Datasets:
pwc-archive
/
links-between-paper-and-code

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/giant-topological-hall-effect-in-van-der
Giant Topological Hall Effect in van der Waals Heterostructures of CrTe2/Bi2Te3
2108.10289
https://arxiv.org/abs/2108.10289v1
https://arxiv.org/pdf/2108.10289v1.pdf
https://github.com/sidambhire/GL-Skyrmion
false
false
true
none
https://paperswithcode.com/paper/manner-multi-view-attention-network-for-noise
MANNER: Multi-view Attention Network for Noise Erasure
2203.02181
https://arxiv.org/abs/2203.02181v1
https://arxiv.org/pdf/2203.02181v1.pdf
https://github.com/winddori2002/MANNER
true
false
true
pytorch
https://paperswithcode.com/paper/speech-text-based-multi-modal-training-with
Speech-text based multi-modal training with bidirectional attention for improved speech recognition
2211.00325
https://arxiv.org/abs/2211.00325v1
https://arxiv.org/pdf/2211.00325v1.pdf
https://github.com/yuhangear/multi-modal-learning
true
true
false
pytorch
https://paperswithcode.com/paper/deep-high-resolution-representation-learning
Deep High-Resolution Representation Learning for Human Pose Estimation
1902.09212
http://arxiv.org/abs/1902.09212v1
http://arxiv.org/pdf/1902.09212v1.pdf
https://github.com/ducongju/HRNet
false
false
true
pytorch
https://paperswithcode.com/paper/bottom-up-higher-resolution-networks-for
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
1908.10357
https://arxiv.org/abs/1908.10357v3
https://arxiv.org/pdf/1908.10357v3.pdf
https://github.com/ducongju/HRNet
false
false
true
pytorch
https://paperswithcode.com/paper/high-resolution-representations-for-labeling
High-Resolution Representations for Labeling Pixels and Regions
1904.04514
http://arxiv.org/abs/1904.04514v1
http://arxiv.org/pdf/1904.04514v1.pdf
https://github.com/ducongju/HRNet
false
false
true
pytorch
https://paperswithcode.com/paper/pytorchdia-a-flexible-gpu-accelerated
PyTorchDIA: A flexible, GPU-accelerated numerical approach to Difference Image Analysis
2104.13715
https://arxiv.org/abs/2104.13715v2
https://arxiv.org/pdf/2104.13715v2.pdf
https://github.com/jah1994/PyTorchDIA
true
true
true
pytorch
https://paperswithcode.com/paper/constructing-long-short-stock-portfolio-with
Constructing long-short stock portfolio with a new listwise learn-to-rank algorithm
2104.12484
https://arxiv.org/abs/2104.12484v1
https://arxiv.org/pdf/2104.12484v1.pdf
https://github.com/TCtobychen/ListFold
true
true
false
pytorch
https://paperswithcode.com/paper/alphanet-improved-training-of-supernet-with
AlphaNet: Improved Training of Supernets with Alpha-Divergence
2102.07954
https://arxiv.org/abs/2102.07954v2
https://arxiv.org/pdf/2102.07954v2.pdf
https://github.com/facebookresearch/AlphaNet
true
true
true
pytorch
https://paperswithcode.com/paper/conservation-laws-for-free-boundary-fluid
Conservation laws for free-boundary fluid layers
2007.05625
https://arxiv.org/abs/2007.05625v2
https://arxiv.org/pdf/2007.05625v2.pdf
https://github.com/bueler/layer-conserve
false
false
true
none
https://paperswithcode.com/paper/dynamic-student-classiffication-on-memory
Dynamic Student Classiffication on Memory Networks for Knowledge Tracing
null
https://link.springer.com/chapter/10.1007/978-3-030-16145-3_13
https://ink.library.smu.edu.sg/sis_research/4347/
https://github.com/simon-tan/DSCMN
true
false
false
tf
https://paperswithcode.com/paper/161009376
FRICAT: A FIRST catalog of FRI radio galaxies
1610.09376
http://arxiv.org/abs/1610.09376v1
http://arxiv.org/pdf/1610.09376v1.pdf
https://github.com/HongmingTang060313/FRDEEP_v2.0
false
false
true
pytorch
https://paperswithcode.com/paper/190311921
Transfer learning for radio galaxy classification
1903.11921
http://arxiv.org/abs/1903.11921v1
http://arxiv.org/pdf/1903.11921v1.pdf
https://github.com/HongmingTang060313/FRDEEP_v2.0
false
false
true
pytorch
https://paperswithcode.com/paper/adversarial-vertex-mixup-toward-better
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization
2003.02484
https://arxiv.org/abs/2003.02484v3
https://arxiv.org/pdf/2003.02484v3.pdf
https://github.com/hirokiadachi/Adversarial-vertex-mixup-pytorch
false
false
true
pytorch
https://paperswithcode.com/paper/lachesis-scalable-asynchronous-bft-on-dag
Lachesis: Scalable Asynchronous BFT on DAG Streams
2108.01900
https://arxiv.org/abs/2108.01900v1
https://arxiv.org/pdf/2108.01900v1.pdf
https://github.com/Fantom-foundation/go-opera
true
true
false
none
https://paperswithcode.com/paper/neural-operator-graph-kernel-network-for
Neural Operator: Graph Kernel Network for Partial Differential Equations
2003.03485
https://arxiv.org/abs/2003.03485v1
https://arxiv.org/pdf/2003.03485v1.pdf
https://github.com/zongyi-li/graph-pde
false
false
true
pytorch
https://paperswithcode.com/paper/convex-parameterization-of-stabilizing
Convex Parameterization of Stabilizing Controllers and its LMI-based Computation via Filtering
2203.17145
https://arxiv.org/abs/2203.17145v1
https://arxiv.org/pdf/2203.17145v1.pdf
https://github.com/soc-ucsd/iop_lmi
true
true
true
none
https://paperswithcode.com/paper/a-deep-q-learning-agent-for-the-l-game-with
A Deep Q-Learning Agent for the L-Game with Variable Batch Training
1802.06225
http://arxiv.org/abs/1802.06225v1
http://arxiv.org/pdf/1802.06225v1.pdf
https://github.com/petrosgk/L-Game-DQN
true
false
false
none
https://paperswithcode.com/paper/genegan-learning-object-transfiguration-and
GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data
1705.04932
http://arxiv.org/abs/1705.04932v1
http://arxiv.org/pdf/1705.04932v1.pdf
https://github.com/megvii-research/genegan
true
false
true
pytorch
https://paperswithcode.com/paper/predicting-semantic-map-representations-from
Predicting Semantic Map Representations from Images using Pyramid Occupancy Networks
2003.13402
https://arxiv.org/abs/2003.13402v1
https://arxiv.org/pdf/2003.13402v1.pdf
https://github.com/tom-roddick/mono-semantic-maps
true
true
true
pytorch
https://paperswithcode.com/paper/contextual-encoder-decoder-network-for-visual
Contextual Encoder-Decoder Network for Visual Saliency Prediction
1902.06634
https://arxiv.org/abs/1902.06634v4
https://arxiv.org/pdf/1902.06634v4.pdf
https://github.com/nvinden/7ChannelEML
false
false
true
tf
https://paperswithcode.com/paper/multi-modal-conditional-bounding-box
Multi-modal Conditional Bounding Box Regression for Music Score Following
2105.04309
https://arxiv.org/abs/2105.04309v1
https://arxiv.org/pdf/2105.04309v1.pdf
https://github.com/CPJKU/cyolo_score_following
true
true
true
pytorch
https://paperswithcode.com/paper/a-deep-reinforcement-learning-approach-to-3
A Deep Reinforcement Learning Approach to Audio-Based Navigation in a Multi-Speaker Environment
2105.04488
https://arxiv.org/abs/2105.04488v1
https://arxiv.org/pdf/2105.04488v1.pdf
https://github.com/petrosgk/AudioRL
true
true
false
none
https://paperswithcode.com/paper/unsupervised-remote-sensing-super-resolution
Unsupervised Remote Sensing Super-Resolution via Migration Image Prior
2105.03579
https://arxiv.org/abs/2105.03579v2
https://arxiv.org/pdf/2105.03579v2.pdf
https://github.com/jiaming-wang/MIP
true
true
false
pytorch
https://paperswithcode.com/paper/crepo-an-open-repository-to-benchmark-credal
CREPO: An Open Repository to Benchmark Credal Network Algorithms
2105.04158
https://arxiv.org/abs/2105.04158v1
https://arxiv.org/pdf/2105.04158v1.pdf
https://github.com/IDSIA/crepo
true
true
false
none
https://paperswithcode.com/paper/360norvic-360-degree-video-classification
360NorVic: 360-Degree Video Classification from Mobile Encrypted Video Traffic
2105.03611
https://arxiv.org/abs/2105.03611v1
https://arxiv.org/pdf/2105.03611v1.pdf
https://github.com/manojMadarasingha/360norvic
true
true
false
none
https://paperswithcode.com/paper/falling-through-the-gaps-neural-architectures
Falling Through the Gaps: Neural Architectures as Models of Morphological Rule Learning
2105.03710
https://arxiv.org/abs/2105.03710v1
https://arxiv.org/pdf/2105.03710v1.pdf
https://github.com/denizbeser/gaps
true
true
false
none
https://paperswithcode.com/paper/spectral-analysis-of-mixing-in-2d-high
Spectral analysis of mixing in 2D high-Reynolds flows
1903.10044
https://arxiv.org/abs/1903.10044v2
https://arxiv.org/pdf/1903.10044v2.pdf
https://github.com/gowtham-ss-ragavan/msub_mdselect_dmd
false
false
true
none
https://paperswithcode.com/paper/exploring-discourse-structures-for-argument
Exploring Discourse Structures for Argument Impact Classification
2106.00976
https://arxiv.org/abs/2106.00976v1
https://arxiv.org/pdf/2106.00976v1.pdf
https://github.com/HKUST-KnowComp/DisCOC
true
true
true
pytorch
https://paperswithcode.com/paper/anonymizing-machine-learning-models
Anonymizing Machine Learning Models
2007.13086
https://arxiv.org/abs/2007.13086v3
https://arxiv.org/pdf/2007.13086v3.pdf
https://github.com/IBM/ai-privacy-toolkit
true
true
false
tf
https://paperswithcode.com/paper/runtime-enforcement-of-hyperproperties
Runtime Enforcement of Hyperproperties
2203.04146
https://arxiv.org/abs/2203.04146v1
https://arxiv.org/pdf/2203.04146v1.pdf
https://github.com/reactive-systems/rehyper
true
true
false
none
https://paperswithcode.com/paper/matrix-product-state-simulations-of-quantum
Matrix product state simulations of quantum quenches and transport in Coulomb blockaded superconducting devices
2207.00948
https://arxiv.org/abs/2207.00948v1
https://arxiv.org/pdf/2207.00948v1.pdf
https://github.com/chiaminchung/quenchtransport
true
true
false
none
https://paperswithcode.com/paper/dmbgn-deep-multi-behavior-graph-networks-for
DMBGN: Deep Multi-Behavior Graph Networks for Voucher Redemption Rate Prediction
2106.03356
https://arxiv.org/abs/2106.03356v1
https://arxiv.org/pdf/2106.03356v1.pdf
https://github.com/fengtong-xiao/DMBGN
true
true
false
pytorch
https://paperswithcode.com/paper/batch-decorrelation-for-active-metric
Batch Decorrelation for Active Metric Learning
2005.10008
https://arxiv.org/abs/2005.10008v2
https://arxiv.org/pdf/2005.10008v2.pdf
https://github.com/kpriyadarshini/BatchAML_Decorrelation
false
false
true
pytorch
https://paperswithcode.com/paper/soft-alignment-objectives-for-robust
Soft Alignment Objectives for Robust Adaptation of Language Generation
2211.16550
https://arxiv.org/abs/2211.16550v2
https://arxiv.org/pdf/2211.16550v2.pdf
https://github.com/mir-mu/softalign_objectives
true
true
true
pytorch
https://paperswithcode.com/paper/adaptive-machine-unlearning
Adaptive Machine Unlearning
2106.04378
https://arxiv.org/abs/2106.04378v1
https://arxiv.org/pdf/2106.04378v1.pdf
https://github.com/ChrisWaites/adaptive-machine-unlearning
true
true
false
jax
https://paperswithcode.com/paper/predicting-bulge-to-total-luminosity-ratio-of
Predicting bulge to total luminosity ratio of galaxies using deep learning
2106.16054
https://arxiv.org/abs/2106.16054v1
https://arxiv.org/pdf/2106.16054v1.pdf
https://github.com/Z3376/Galaxy_BT_Prediction
true
true
false
none
https://paperswithcode.com/paper/session-based-recommendations-with-recurrent
Session-based Recommendations with Recurrent Neural Networks
1511.06939
http://arxiv.org/abs/1511.06939v4
http://arxiv.org/pdf/1511.06939v4.pdf
https://github.com/yhs968/pyGRU4REC
false
false
true
pytorch
https://paperswithcode.com/paper/bridging-pre-trained-models-and-downstream
Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding
2112.02268
https://arxiv.org/abs/2112.02268v2
https://arxiv.org/pdf/2112.02268v2.pdf
https://github.com/wangdeze18/DACL
true
true
false
pytorch
https://paperswithcode.com/paper/simplifying-deep-reinforcement-learning-via
Simplifying Deep Reinforcement Learning via Self-Supervision
2106.05526
https://arxiv.org/abs/2106.05526v1
https://arxiv.org/pdf/2106.05526v1.pdf
https://github.com/daochenzha/SSRL
true
true
true
tf
https://paperswithcode.com/paper/draco-weakly-supervised-dense-reconstruction
DRACO: Weakly Supervised Dense Reconstruction And Canonicalization of Objects
2011.12912
https://arxiv.org/abs/2011.12912v1
https://arxiv.org/pdf/2011.12912v1.pdf
https://github.com/RahulSajnani/DRACO-Weakly-Supervised-Dense-Reconstruction-And-Canonicalization-of-Objects
true
false
false
pytorch
https://paperswithcode.com/paper/reverberation-mapping-of-two-luminous-quasars
Reverberation Mapping of Two Luminous Quasars: the Broad-line Region Structure and Black Hole Mass
2106.05655
https://arxiv.org/abs/2106.05655v1
https://arxiv.org/pdf/2106.05655v1.pdf
https://github.com/PuDu-Astro/DASpec
true
true
false
none
https://paperswithcode.com/paper/retinanet-object-detector-based-on-analog-to
RetinaNet Object Detector based on Analog-to-Spiking Neural Network Conversion
2106.05624
https://arxiv.org/abs/2106.05624v2
https://arxiv.org/pdf/2106.05624v2.pdf
https://github.com/joaromi/Spiking-RetinaNet
true
true
true
tf
https://paperswithcode.com/paper/lyman-alpha-absorption-beyond-the-disk-of
Lyman-\alpha absorption beyond the disk of simulated spiral galaxies
2005.08580
http://arxiv.org/abs/2005.08580v1
http://arxiv.org/pdf/2005.08580v1.pdf
https://bitbucket.org/broett/pygad
true
true
true
none
https://paperswithcode.com/paper/dynamic-routing-between-capsules
Dynamic Routing Between Capsules
1710.09829
http://arxiv.org/abs/1710.09829v2
http://arxiv.org/pdf/1710.09829v2.pdf
https://github.com/Egesabanci/capsuleNetworks
false
false
true
tf
https://paperswithcode.com/paper/supervised-video-summarization-via-multiple
Supervised Video Summarization via Multiple Feature Sets with Parallel Attention
2104.11530
https://arxiv.org/abs/2104.11530v2
https://arxiv.org/pdf/2104.11530v2.pdf
https://github.com/StevRamos/video_summarization
false
false
false
pytorch
https://paperswithcode.com/paper/training-data-efficient-image-transformers
Training data-efficient image transformers & distillation through attention
2012.12877
https://arxiv.org/abs/2012.12877v2
https://arxiv.org/pdf/2012.12877v2.pdf
https://github.com/omihub777/vit-cifar
false
false
true
pytorch
https://paperswithcode.com/paper/deep-biaffine-attention-for-neural-dependency
Deep Biaffine Attention for Neural Dependency Parsing
1611.01734
http://arxiv.org/abs/1611.01734v3
http://arxiv.org/pdf/1611.01734v3.pdf
https://github.com/XuezheMax/NeuroNLP2
false
false
true
pytorch
https://paperswithcode.com/paper/structure-regularized-attention-for
Structure-Regularized Attention for Deformable Object Representation
2106.06672
https://arxiv.org/abs/2106.06672v1
https://arxiv.org/pdf/2106.06672v1.pdf
https://github.com/shenao-zhang/StRA
true
true
false
pytorch
https://paperswithcode.com/paper/yolo9000-better-faster-stronger
YOLO9000: Better, Faster, Stronger
1612.08242
http://arxiv.org/abs/1612.08242v1
http://arxiv.org/pdf/1612.08242v1.pdf
https://github.com/Qengineering/YoloV2-ncnn-Raspberry-Pi-4
false
false
true
none
https://paperswithcode.com/paper/psychometric-predictive-power-of-large
Psychometric Predictive Power of Large Language Models
2311.07484
https://arxiv.org/abs/2311.07484v3
https://arxiv.org/pdf/2311.07484v3.pdf
https://github.com/kuribayashi4/llm-cognitive-modeling
true
true
true
pytorch
https://paperswithcode.com/paper/improving-bridge-estimators-via-f-gan
Improving Bridge estimators via $f$-GAN
2106.07462
https://arxiv.org/abs/2106.07462v3
https://arxiv.org/pdf/2106.07462v3.pdf
https://github.com/hwxing3259/Bridge_sampling_and_fGAN
true
true
false
pytorch
https://paperswithcode.com/paper/a-modified-wind-driven-optimization-model-for
A Modified Wind Driven Optimization Model for Global Continuous Optimization
null
https://www.researchgate.net/publication/282680554_A_Modified_Wind_Driven_Optimization_Model_for_Global_Continuous_Optimization
https://link.springer.com/chapter/10.1007%2F978-3-319-19644-2_25
https://github.com/boulesnane/Modified-WDO
false
false
false
none
https://paperswithcode.com/paper/a-powerful-genetic-algorithm-for-traveling
A Powerful Genetic Algorithm for Traveling Salesman Problem
1402.4699
http://arxiv.org/abs/1402.4699v1
http://arxiv.org/pdf/1402.4699v1.pdf
https://github.com/sugia/GA-for-TSP
true
true
true
none
https://paperswithcode.com/paper/ttopt-a-maximum-volume-quantized-tensor-train
TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning
2205.00293
https://arxiv.org/abs/2205.00293v2
https://arxiv.org/pdf/2205.00293v2.pdf
https://github.com/andreichertkov/ttopt
true
true
true
none
https://paperswithcode.com/paper/provably-robust-classification-of-adversarial
Provably robust classification of adversarial examples with detection
null
https://openreview.net/forum?id=sRA5rLNpmQc
https://openreview.net/pdf?id=sRA5rLNpmQc
https://github.com/boschresearch/robust_classification_with_detection
true
false
false
pytorch
https://paperswithcode.com/paper/a-containerized-proof-of-concept
A containerized proof-of-concept implementation of LightChain system
2007.13203
http://arxiv.org/abs/2007.13203v1
http://arxiv.org/pdf/2007.13203v1.pdf
https://github.com/yhassanzadeh13/lightchain-container
true
true
true
none
https://paperswithcode.com/paper/fishermask-enhancing-neural-network-labeling
FisherMask: Enhancing Neural Network Labeling Efficiency in Image Classification Using Fisher Information
2411.05752
https://arxiv.org/abs/2411.05752v1
https://arxiv.org/pdf/2411.05752v1.pdf
https://github.com/sgchr273/fishermask
true
true
false
pytorch
https://paperswithcode.com/paper/the-ham10000-dataset-a-large-collection-of
The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
1803.10417
http://arxiv.org/abs/1803.10417v3
http://arxiv.org/pdf/1803.10417v3.pdf
https://github.com/skrantidatta/Attention-based-Skin-Cancer-Classification
false
false
true
tf
https://paperswithcode.com/paper/automated-mining-of-leaderboards-for
Automated Mining of Leaderboards for Empirical AI Research
2109.13089
https://arxiv.org/abs/2109.13089v1
https://arxiv.org/pdf/2109.13089v1.pdf
https://github.com/kabongosalomon/task-dataset-metric-nli-extraction
true
true
false
pytorch
https://paperswithcode.com/paper/ladder-variational-autoencoders
Ladder Variational Autoencoders
1602.02282
http://arxiv.org/abs/1602.02282v3
http://arxiv.org/pdf/1602.02282v3.pdf
https://github.com/simonamtoft/ml-library
false
false
true
pytorch
https://paperswithcode.com/paper/doubly-robust-policy-evaluation-and-learning
Doubly Robust Policy Evaluation and Learning
1103.4601
https://arxiv.org/abs/1103.4601v2
https://arxiv.org/pdf/1103.4601v2.pdf
https://github.com/leoguelman/BLBF
false
false
true
pytorch
https://paperswithcode.com/paper/neural-graph-collaborative-filtering
Neural Graph Collaborative Filtering
1905.08108
https://arxiv.org/abs/1905.08108v2
https://arxiv.org/pdf/1905.08108v2.pdf
https://github.com/zzz2010/ngcf-paddle2
false
false
true
paddle
https://paperswithcode.com/paper/music-classification-beyond-supervised
Music Classification: Beyond Supervised Learning, Towards Real-world Applications
2111.11636
https://arxiv.org/abs/2111.11636v2
https://arxiv.org/pdf/2111.11636v2.pdf
https://github.com/music-classification/tutorial
true
true
false
pytorch
https://paperswithcode.com/paper/model-explanations-via-the-axiomatic-causal
Model Explanations via the Axiomatic Causal Lens
2109.03890
https://arxiv.org/abs/2109.03890v6
https://arxiv.org/pdf/2109.03890v6.pdf
https://github.com/gabi-1337/causal-explanations
true
true
true
none
https://paperswithcode.com/paper/effects-of-personality-traits-in-predicting
Effects of personality traits in predicting grade retention of Brazilian students
2107.05767
https://arxiv.org/abs/2107.05767v1
https://arxiv.org/pdf/2107.05767v1.pdf
https://github.com/Lucka-Gianvechio/LatinX-Grade-Retention-Paper
true
true
false
none
https://paperswithcode.com/paper/surface-detection-for-sketched-single-photon
Surface Detection for Sketched Single Photon Lidar
2105.06920
https://arxiv.org/abs/2105.06920v1
https://arxiv.org/pdf/2105.06920v1.pdf
https://gitlab.com/Tachella/sketched_lidar
false
false
true
none
https://paperswithcode.com/paper/learning-multi-touch-conversion-attribution
Learning Multi-touch Conversion Attribution with Dual-attention Mechanisms for Online Advertising
1808.03737
http://arxiv.org/abs/1808.03737v2
http://arxiv.org/pdf/1808.03737v2.pdf
https://github.com/rk2900/deep-conv-attr
true
true
true
tf
https://paperswithcode.com/paper/a-sensitivity-study-of-vbs-and-diboson-ww-to
A sensitivity study of VBS and diboson WW to dimension-6 EFT operators at the LHC
2108.03199
https://arxiv.org/abs/2108.03199v3
https://arxiv.org/pdf/2108.03199v3.pdf
https://github.com/MultibosonEFTStudies/D6EFTPaperPlots
true
true
false
none
https://paperswithcode.com/paper/generalized-wasserstein-dice-loss-test-time
Generalized Wasserstein Dice Loss, Test-time Augmentation, and Transformers for the BraTS 2021 challenge
2112.13054
https://arxiv.org/abs/2112.13054v1
https://arxiv.org/pdf/2112.13054v1.pdf
https://github.com/lucasfidon/trabit_brats2021
true
true
true
pytorch
https://paperswithcode.com/paper/putting-nerf-on-a-diet-semantically
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis
2104.00677
https://arxiv.org/abs/2104.00677v1
https://arxiv.org/pdf/2104.00677v1.pdf
https://github.com/codestella/putting-nerf-on-a-diet
false
false
true
jax
https://paperswithcode.com/paper/incremental-training-of-graph-neural-networks
Lifelong Learning of Graph Neural Networks for Open-World Node Classification
2006.14422
https://arxiv.org/abs/2006.14422v4
https://arxiv.org/pdf/2006.14422v4.pdf
https://github.com/lgalke/lifelong-learning
true
true
true
pytorch
https://paperswithcode.com/paper/human-in-the-loop-for-data-collection-a-multi
Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech
2107.08720
https://arxiv.org/abs/2107.08720v1
https://arxiv.org/pdf/2107.08720v1.pdf
https://github.com/marcoguerini/CONAN
true
true
false
none
https://paperswithcode.com/paper/vw-sdk-efficient-convolutional-weight-mapping
VW-SDK: Efficient Convolutional Weight Mapping Using Variable Windows for Processing-In-Memory Architectures
2112.11282
https://arxiv.org/abs/2112.11282v1
https://arxiv.org/pdf/2112.11282v1.pdf
https://github.com/djwhsdj/vw-sdk
true
true
false
none
https://paperswithcode.com/paper/sailor-scaling-anchors-via-insights-into
SAILOR: Scaling Anchors via Insights into Latent Object Representation
2210.07811
https://arxiv.org/abs/2210.07811v2
https://arxiv.org/pdf/2210.07811v2.pdf
https://github.com/malicd/sailor
true
true
true
pytorch
https://paperswithcode.com/paper/adaptive-multilevel-monte-carlo-for
Adaptive Multilevel Monte Carlo for Probabilities
2107.09148
https://arxiv.org/abs/2107.09148v1
https://arxiv.org/pdf/2107.09148v1.pdf
https://github.com/JSpence97/mlmc-for-probabilities
true
true
false
none
https://paperswithcode.com/paper/emotion-recognition-based-on-multi-task
Multi-Task Learning Framework for Emotion Recognition in-the-wild
2207.09373
https://arxiv.org/abs/2207.09373v3
https://arxiv.org/pdf/2207.09373v3.pdf
https://github.com/AIM3-RUC/ABAW4
true
true
true
pytorch
https://paperswithcode.com/paper/opengcd-assisting-open-world-recognition-with
OpenGCD: Assisting Open World Recognition with Generalized Category Discovery
2308.06926
https://arxiv.org/abs/2308.06926v1
https://arxiv.org/pdf/2308.06926v1.pdf
https://github.com/fulin-gao/opengcd
true
true
false
pytorch
https://paperswithcode.com/paper/openba-v2-reaching-77-3-high-compression
OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning
2405.05957
https://arxiv.org/abs/2405.05957v1
https://arxiv.org/pdf/2405.05957v1.pdf
https://github.com/opennlg/openba-v2
true
true
false
pytorch
https://paperswithcode.com/paper/mastering-chess-and-shogi-by-self-play-with-a
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
1712.01815
http://arxiv.org/abs/1712.01815v1
http://arxiv.org/pdf/1712.01815v1.pdf
https://github.com/saikrishna-1996/deep_pepper_chess
false
false
true
pytorch
https://paperswithcode.com/paper/an-open-source-bayesian-atmospheric-radiative
An open-source Bayesian atmospheric radiative transfer (BART) code: III. Initialization, atmospheric profile generator, post-processing routines, and application to exoplanet WASP-43b
2104.12525
https://arxiv.org/abs/2104.12525v1
https://arxiv.org/pdf/2104.12525v1.pdf
https://github.com/pcubillos/mc3
true
true
false
none
https://paperswithcode.com/paper/experimental-validation-of-fastcat-kv-and-mv
Experimental validation of Fastcat kV and MV cone beam CT (CBCT) simulator
2104.13885
https://arxiv.org/abs/2104.13885v1
https://arxiv.org/pdf/2104.13885v1.pdf
https://github.com/jerichooconnell/fastCAT
true
true
false
none
https://paperswithcode.com/paper/socluster-towards-intent-based-clustering-of
SOCluster- Towards Intent-based Clustering of Stack Overflow Questions using Graph-Based Approach
2107.02399
https://arxiv.org/abs/2107.02399v1
https://arxiv.org/pdf/2107.02399v1.pdf
https://github.com/Liveitabhi/SOCluster
true
true
false
none
https://paperswithcode.com/paper/soteria-provable-defense-against-privacy
Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective
null
http://openaccess.thecvf.com//content/CVPR2021/html/Sun_Soteria_Provable_Defense_Against_Privacy_Leakage_in_Federated_Learning_From_CVPR_2021_paper.html
http://openaccess.thecvf.com//content/CVPR2021/papers/Sun_Soteria_Provable_Defense_Against_Privacy_Leakage_in_Federated_Learning_From_CVPR_2021_paper.pdf
https://github.com/jeremy313/Soteria
true
true
false
pytorch
https://paperswithcode.com/paper/zero-bias-deep-learning-enabled-quick-and
Zero-bias Deep Learning Enabled Quick and Reliable Abnormality Detection in IoT
2105.15098
https://arxiv.org/abs/2105.15098v1
https://arxiv.org/pdf/2105.15098v1.pdf
https://github.com/pcwhy/AbnormalityDetectionInZbDNN
true
true
false
none
https://paperswithcode.com/paper/machine-learning-accelerated-particle-in-cell
Machine learning accelerated particle-in-cell plasma simulations
2110.12444
https://arxiv.org/abs/2110.12444v1
https://arxiv.org/pdf/2110.12444v1.pdf
https://github.com/rkube/picfun
true
true
true
none
https://paperswithcode.com/paper/synergy-between-observation-systems-oceanic
Synergy between Observation Systems Oceanic in Turbulent Regions
2012.14516
https://arxiv.org/abs/2012.14516v2
https://arxiv.org/pdf/2012.14516v2.pdf
https://github.com/v18nguye/gulfstream-lrm
true
true
false
pytorch
https://paperswithcode.com/paper/rkappa-software-for-analyzing-rule-based
RKappa: Software for Analyzing Rule-Based Models
1809.08214
http://arxiv.org/abs/1809.08214v1
http://arxiv.org/pdf/1809.08214v1.pdf
https://github.com/lptolik/R4Kappa
true
true
false
none
https://paperswithcode.com/paper/bareb-a-bayesian-repulsive-biclustering-model
BAREB: A Bayesian repulsive biclustering model for periodontal data
1902.05680
http://arxiv.org/abs/1902.05680v2
http://arxiv.org/pdf/1902.05680v2.pdf
https://github.com/YanxunXu/BAREB
true
true
false
none
https://paperswithcode.com/paper/encoding-category-trees-into-word-embeddings
Encoding Category Trees Into Word-Embeddings Using Geometric Approach
null
https://openreview.net/forum?id=rJlWOj0qF7
https://openreview.net/pdf?id=rJlWOj0qF7
https://github.com/gnodisnait/bp94nball
true
true
false
none
https://paperswithcode.com/paper/interlinking-iconclass-data-with-concepts-of
Interlinking Iconclass Data with Concepts of Art \& Architecture Thesaurus
null
https://aclanthology.org/2020.ai4hi-1.2
https://aclanthology.org/2020.ai4hi-1.2.pdf
https://github.com/annabreit/taxonomy-interlinking
true
true
false
none
https://paperswithcode.com/paper/a-graph-neural-network-approach-for-scalable
A Graph Neural Network Approach for Scalable Wireless Power Control
1907.08487
https://arxiv.org/abs/1907.08487v1
https://arxiv.org/pdf/1907.08487v1.pdf
https://github.com/yshenaw/Globecom2019
true
true
false
none
https://paperswithcode.com/paper/stochastic-function-norm-regularization-of
Stochastic Function Norm Regularization of Deep Networks
1605.09085
https://arxiv.org/abs/1605.09085v3
https://arxiv.org/pdf/1605.09085v3.pdf
https://github.com/AmalRT/DNN_Reg
true
true
false
none
https://paperswithcode.com/paper/mri-super-resolution-using-multi-channel
MRI Super-Resolution using Multi-Channel Total Variation
1810.03422
https://arxiv.org/abs/1810.03422v6
https://arxiv.org/pdf/1810.03422v6.pdf
https://github.com/WCHN/CA_MTV-preproc
true
true
true
none
https://paperswithcode.com/paper/mpi-multi-receptive-and-parallel-integration
MPI: Multi-receptive and Parallel Integration for Salient Object Detection
2108.03618
https://arxiv.org/abs/2108.03618v1
https://arxiv.org/pdf/2108.03618v1.pdf
https://github.com/nuaacj/mpi
true
true
false
pytorch
https://paperswithcode.com/paper/distributionally-robust-segmentation-of
Distributionally Robust Segmentation of Abnormal Fetal Brain 3D MRI
2108.04175
https://arxiv.org/abs/2108.04175v1
https://arxiv.org/pdf/2108.04175v1.pdf
https://github.com/LucasFidon/HardnessWeightedSampler
true
true
false
pytorch
https://paperswithcode.com/paper/deep-neural-network-predicts-parameters-of
Deep learning Local Reduced Density Matrices for Many-body Hamiltonian Estimation
2012.03019
https://arxiv.org/abs/2012.03019v2
https://arxiv.org/pdf/2012.03019v2.pdf
https://github.com/joyebnu/qubismnet
true
true
true
none
https://paperswithcode.com/paper/lights-camera-action-a-framework-to-improve
Lights, Camera, Action! A Framework to Improve NLP Accuracy over OCR documents
2108.02899
https://arxiv.org/abs/2108.02899v1
https://arxiv.org/pdf/2108.02899v1.pdf
https://github.com/microsoft/genalog
true
true
true
none
https://paperswithcode.com/paper/the-cosmic-linear-anisotropy-solving-system-1
The Cosmic Linear Anisotropy Solving System (CLASS) II: Approximation schemes
1104.2933
http://arxiv.org/abs/1104.2933v3
http://arxiv.org/pdf/1104.2933v3.pdf
https://github.com/AbhishDev/Neutrino_Decay
false
false
true
none
https://paperswithcode.com/paper/how-to-make-an-image-more-memorable-a-deep
How to Make an Image More Memorable? A Deep Style Transfer Approach
1704.01745
http://arxiv.org/abs/1704.01745v1
http://arxiv.org/pdf/1704.01745v1.pdf
https://github.com/aliaksandrsiarohin/mem-transfer
false
false
true
torch