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

Dataset card Data Studio Files
xet
Community
1
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36
81
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242
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https://paperswithcode.com/paper/social-attention-modeling-attention-in-human
Social Attention: Modeling Attention in Human Crowds
1710.04689
http://arxiv.org/abs/1710.04689v2
http://arxiv.org/pdf/1710.04689v2.pdf
https://github.com/huang-xx/STGAT
false
false
true
pytorch
https://paperswithcode.com/paper/multi-agent-actor-critic-for-mixed
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
1706.02275
https://arxiv.org/abs/1706.02275v4
https://arxiv.org/pdf/1706.02275v4.pdf
https://github.com/Ah31/maddpg_pytorch
false
false
true
pytorch
https://paperswithcode.com/paper/image-super-resolution-using-very-deep
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
1807.02758
http://arxiv.org/abs/1807.02758v2
http://arxiv.org/pdf/1807.02758v2.pdf
https://github.com/dongheehand/RCAN-tf
false
false
true
tf
https://paperswithcode.com/paper/vox2vox-3d-gan-for-brain-tumour-segmentation
Vox2Vox: 3D-GAN for Brain Tumour Segmentation
2003.13653
https://arxiv.org/abs/2003.13653v3
https://arxiv.org/pdf/2003.13653v3.pdf
https://github.com/enochkan/vox2vox
false
false
true
pytorch
https://paperswithcode.com/paper/domain-generalization-by-solving-jigsaw
Domain Generalization by Solving Jigsaw Puzzles
1903.06864
http://arxiv.org/abs/1903.06864v2
http://arxiv.org/pdf/1903.06864v2.pdf
https://github.com/Emma0118/domain-generalization
false
false
true
pytorch
https://paperswithcode.com/paper/reducing-disparate-exposure-in-ranking-a
Reducing Disparate Exposure in Ranking: A Learning To Rank Approach
1805.08716
https://arxiv.org/abs/1805.08716v5
https://arxiv.org/pdf/1805.08716v5.pdf
https://github.com/fair-search/fairsearchdeltr-elasticsearch-plugin
false
false
true
none
https://paperswithcode.com/paper/memory-oriented-decoder-for-light-field
Memory-oriented Decoder for Light Field Salient Object Detection
null
http://papers.nips.cc/paper/8376-memory-oriented-decoder-for-light-field-salient-object-detection
http://papers.nips.cc/paper/8376-memory-oriented-decoder-for-light-field-salient-object-detection.pdf
https://github.com/OIPLab-DUT/MoLF
true
true
false
none
https://paperswithcode.com/paper/making-the-cut-a-bandit-based-approach-to
Making the Cut: A Bandit-based Approach to Tiered Interviewing
1906.09621
https://arxiv.org/abs/1906.09621v2
https://arxiv.org/pdf/1906.09621v2.pdf
https://github.com/principledhiring/TieredHiring
true
false
false
none
https://paperswithcode.com/paper/speech-commands-a-dataset-for-limited
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
1804.03209
http://arxiv.org/abs/1804.03209v1
http://arxiv.org/pdf/1804.03209v1.pdf
https://github.com/qute012/Wav2Keyword
false
false
true
pytorch
https://paperswithcode.com/paper/efficiently-avoiding-saddle-points-with-zero
Efficiently avoiding saddle points with zero order methods: No gradients required
1910.13021
https://arxiv.org/abs/1910.13021v1
https://arxiv.org/pdf/1910.13021v1.pdf
https://github.com/lamflokas/zero-order
true
false
false
none
https://paperswithcode.com/paper/190600569
Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards
1906.00569
https://arxiv.org/abs/1906.00569v1
https://arxiv.org/pdf/1906.00569v1.pdf
https://github.com/akagrecha/Neurips-2019-simulations
true
false
false
none
https://paperswithcode.com/paper/the-gap-on-gap-tackling-the-problem-of
The Gap on GAP: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets
2011.01837
https://arxiv.org/abs/2011.01837v3
https://arxiv.org/pdf/2011.01837v3.pdf
https://github.com/vid-koci/weightingGAP
true
true
true
none
https://paperswithcode.com/paper/70-years-of-machine-learning-in-geoscience-in
70 years of machine learning in geoscience in review
2006.13311
https://arxiv.org/abs/2006.13311v3
https://arxiv.org/pdf/2006.13311v3.pdf
https://github.com/JesperDramsch/70-Years-of-Machine-Learning-in-Geoscience-in-Review
true
false
true
none
https://paperswithcode.com/paper/recovering-bandits
Recovering Bandits
1910.14354
https://arxiv.org/abs/1910.14354v1
https://arxiv.org/pdf/1910.14354v1.pdf
https://github.com/ciarapb/recovering_bandits
true
false
false
none
https://paperswithcode.com/paper/nonparametric-spherical-topic-modeling-with
Nonparametric Spherical Topic Modeling with Word Embeddings
1604.00126
http://arxiv.org/abs/1604.00126v1
http://arxiv.org/pdf/1604.00126v1.pdf
https://github.com/Ardavans/sHDP
false
false
true
none
https://paperswithcode.com/paper/revisiting-spatial-temporal-similarity-a-deep
Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction
1803.01254
http://arxiv.org/abs/1803.01254v2
http://arxiv.org/pdf/1803.01254v2.pdf
https://github.com/zzwells/jdd2018-population-forecast
false
false
true
tf
https://paperswithcode.com/paper/you-only-look-once-unified-real-time-object
You Only Look Once: Unified, Real-Time Object Detection
1506.02640
http://arxiv.org/abs/1506.02640v5
http://arxiv.org/pdf/1506.02640v5.pdf
https://github.com/gary-kaitung/data-science-portfolio
false
false
true
tf
https://paperswithcode.com/paper/a-neural-algorithm-of-artistic-style
A Neural Algorithm of Artistic Style
1508.06576
http://arxiv.org/abs/1508.06576v2
http://arxiv.org/pdf/1508.06576v2.pdf
https://github.com/gary-kaitung/data-science-portfolio
false
false
true
tf
https://paperswithcode.com/paper/facenet-a-unified-embedding-for-face
FaceNet: A Unified Embedding for Face Recognition and Clustering
1503.03832
http://arxiv.org/abs/1503.03832v3
http://arxiv.org/pdf/1503.03832v3.pdf
https://github.com/gary-kaitung/data-science-portfolio
false
false
true
tf
https://paperswithcode.com/paper/lessons-from-the-b-0-to-k-0-m-m-angular
Lessons from the $B^{0,+}\to K^{*0,+}μ^+μ^-$ angular analyses
2011.01212
https://arxiv.org/abs/2011.01212v2
https://arxiv.org/pdf/2011.01212v2.pdf
https://github.com/silvest/HEPfit
true
false
false
none
https://paperswithcode.com/paper/what-do-you-mean-why-resolving-sluices-in
What Do You Mean `Why?': Resolving Sluices in Conversations
1911.09478
https://arxiv.org/abs/1911.09478v1
https://arxiv.org/pdf/1911.09478v1.pdf
https://github.com/vpetren/conv_sluice_resolution
true
true
true
none
https://paperswithcode.com/paper/fast-spatial-autocorrelation
Fast Spatial Autocorrelation
2010.08676
https://arxiv.org/abs/2010.08676v1
https://arxiv.org/pdf/2010.08676v1.pdf
https://github.com/aamgalan/spatial_autocorrelation
true
true
true
none
https://paperswithcode.com/paper/rezero-is-all-you-need-fast-convergence-at
ReZero is All You Need: Fast Convergence at Large Depth
2003.04887
https://arxiv.org/abs/2003.04887v2
https://arxiv.org/pdf/2003.04887v2.pdf
https://github.com/tbachlechner/ReZero-examples
false
false
true
pytorch
https://paperswithcode.com/paper/llsf-learning-label-specific-features-for
LLSF - Learning Label Specific Features for Multi-Label Classifcation
null
https://ieeexplore.ieee.org/document/7373322
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7373322
https://github.com/Prady029/LLSF-Learning-Label-Specific-Features-for-Multi-Label-Classifcation
false
false
false
none
https://paperswithcode.com/paper/a-comparative-study-of-machine-learning-1
A Comparative Study of Machine Learning Models for Predicting the State of Reactive Mixing
2002.11511
https://arxiv.org/abs/2002.11511v1
https://arxiv.org/pdf/2002.11511v1.pdf
https://github.com/bulbulahmmed/ML-to-reactive-mixing-data
true
true
false
none
https://paperswithcode.com/paper/squeezed-states-of-light-and-their
Squeezed states of light and their applications in laser interferometers
1611.03986
https://arxiv.org/abs/1611.03986v3
https://arxiv.org/pdf/1611.03986v3.pdf
https://github.com/dstei/sqz-visualisation
false
false
true
none
https://paperswithcode.com/paper/adaptive-weighted-nonnegative-matrix
Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature Representation
2206.03020
https://arxiv.org/abs/2206.03020v1
https://arxiv.org/pdf/2206.03020v1.pdf
https://github.com/wrnmf/robustnmf
true
true
false
none
https://paperswithcode.com/paper/reweighted-wake-sleep
Reweighted Wake-Sleep
1406.2751
http://arxiv.org/abs/1406.2751v4
http://arxiv.org/pdf/1406.2751v4.pdf
https://github.com/jbornschein/reweighted-ws
true
true
true
none
https://paperswithcode.com/paper/multi-hop-selector-network-for-multi-turn
Multi-hop Selector Network for Multi-turn Response Selection in Retrieval-based Chatbots
null
https://aclanthology.org/D19-1011
https://aclanthology.org/D19-1011.pdf
https://github.com/chunyuanY/Dialogue
false
false
false
pytorch
https://paperswithcode.com/paper/b-anomalies-under-the-lens-of-electroweak
$B$ anomalies under the lens of electroweak precision
2007.04400
https://arxiv.org/abs/2007.04400v2
https://arxiv.org/pdf/2007.04400v2.pdf
https://github.com/silvest/HEPfit
true
false
false
none
https://paperswithcode.com/paper/pseudo-cts-from-t1-weighted-mri-for-planning
Pseudo-CTs from T1-weighted MRI for planning of low-intensity transcranial focused ultrasound neuromodulation: an open-source tool
2209.12031
https://arxiv.org/abs/2209.12031v1
https://arxiv.org/pdf/2209.12031v1.pdf
https://github.com/sitiny/mr-to-pct
true
true
false
pytorch
https://paperswithcode.com/paper/causal-inference-with-the-instrumental
Causal Inference with the Instrumental Variable Approach and Bayesian Nonparametric Machine Learning
2102.01199
https://arxiv.org/abs/2102.01199v1
https://arxiv.org/pdf/2102.01199v1.pdf
https://github.com/rsparapa/bnptools
true
true
false
none
https://paperswithcode.com/paper/quantum-overlapping-tomography
Quantum Overlapping Tomography
1908.02754
https://arxiv.org/abs/1908.02754v2
https://arxiv.org/pdf/1908.02754v2.pdf
https://github.com/tehruhn/quantum-overlapping-tomo
false
false
true
none
https://paperswithcode.com/paper/summit-a-simulator-for-urban-driving-in
SUMMIT: A Simulator for Urban Driving in Massive Mixed Traffic
1911.04074
https://arxiv.org/abs/1911.04074v1
https://arxiv.org/pdf/1911.04074v1.pdf
https://github.com/AdaCompNUS/summit
false
false
true
none
https://paperswithcode.com/paper/artificial-intelligence-for-detection-and
Artificial intelligence for detection and quantification of rust and leaf miner in coffee crop
2103.11241
https://arxiv.org/abs/2103.11241v2
https://arxiv.org/pdf/2103.11241v2.pdf
https://github.com/Lucs1590/Coffee_Recognize
true
false
false
none
https://paperswithcode.com/paper/deep-audio-visual-speech-recognition
Deep Audio-Visual Speech Recognition
1809.02108
http://arxiv.org/abs/1809.02108v2
http://arxiv.org/pdf/1809.02108v2.pdf
https://github.com/amitai1992/AutomatedLipReading
false
false
true
none
https://paperswithcode.com/paper/progressive-training-of-multi-level-wavelet
Progressive Training of Multi-level Wavelet Residual Networks for Image Denoising
2010.12422
https://arxiv.org/abs/2010.12422v1
https://arxiv.org/pdf/2010.12422v1.pdf
https://github.com/happycaoyue/PT-MWRN
true
true
false
pytorch
https://paperswithcode.com/paper/rescuing-neural-spike-train-models-from-bad
Rescuing neural spike train models from bad MLE
2010.12362
https://arxiv.org/abs/2010.12362v1
https://arxiv.org/pdf/2010.12362v1.pdf
https://github.com/diegoarri91/mmd-glm
true
true
false
pytorch
https://paperswithcode.com/paper/deep-autoregressive-neural-networks-for-high
Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identification
1812.09444
http://arxiv.org/abs/1812.09444v1
http://arxiv.org/pdf/1812.09444v1.pdf
https://github.com/cics-nd/cnn-inversion
true
true
false
pytorch
https://paperswithcode.com/paper/attention-is-all-you-need
Attention Is All You Need
1706.03762
https://arxiv.org/abs/1706.03762v7
https://arxiv.org/pdf/1706.03762v7.pdf
https://github.com/davidalbertonogueira/NLP-tutorials
false
false
true
pytorch
https://paperswithcode.com/paper/high-resolution-neural-texture-synthesis-with
High resolution neural texture synthesis with long range constraints
2008.01808
https://arxiv.org/abs/2008.01808v1
https://arxiv.org/pdf/2008.01808v1.pdf
https://github.com/nicaogr/multiresolution_texture
true
false
true
tf
https://paperswithcode.com/paper/diffusion-variational-autoencoders
Diffusion Variational Autoencoders
1901.08991
http://arxiv.org/abs/1901.08991v2
http://arxiv.org/pdf/1901.08991v2.pdf
https://github.com/luis-armando-perez-rey/diffusion_vae_github
false
false
true
tf
https://paperswithcode.com/paper/light-weight-retinanet-for-object-detection
Light-Weight RetinaNet for Object Detection
1905.10011
https://arxiv.org/abs/1905.10011v1
https://arxiv.org/pdf/1905.10011v1.pdf
https://github.com/PSCLab-ASU/LW-RetinaNet
true
true
true
none
https://paperswithcode.com/paper/self-paced-multi-label-learning-with
Self-Paced Multi-Label Learning with Diversity
1910.03497
https://arxiv.org/abs/1910.03497v1
https://arxiv.org/pdf/1910.03497v1.pdf
https://github.com/amjadseyedi/SPMLD
true
true
true
none
https://paperswithcode.com/paper/context-tree-for-adaptive-session-based
Context Tree for Adaptive Session-based Recommendation
1806.03733
http://arxiv.org/abs/1806.03733v1
http://arxiv.org/pdf/1806.03733v1.pdf
https://github.com/MiFei/Context-Tree
false
false
true
none
https://paperswithcode.com/paper/an-environmental-monitoring-network-for
An Environmental Monitoring Network for Quantum Gas Experiments and Devices
2101.12726
https://arxiv.org/abs/2101.12726v2
https://arxiv.org/pdf/2101.12726v2.pdf
https://github.com/tjb36/barrett2021_monitoring_network
true
true
true
none
https://paperswithcode.com/paper/robust-and-communication-efficient-federated
Robust and Communication-Efficient Federated Learning from Non-IID Data
1903.02891
http://arxiv.org/abs/1903.02891v1
http://arxiv.org/pdf/1903.02891v1.pdf
https://github.com/felisat/federated-learning
false
false
true
pytorch
https://paperswithcode.com/paper/tlgan-document-text-localization-using
TLGAN: document Text Localization using Generative Adversarial Nets
2010.11547
https://arxiv.org/abs/2010.11547v1
https://arxiv.org/pdf/2010.11547v1.pdf
https://github.com/SYR-Aegis/BrailleOCR
false
false
true
pytorch
https://paperswithcode.com/paper/large-margin-softmax-loss-for-speaker
Large Margin Softmax Loss for Speaker Verification
1904.03479
https://arxiv.org/abs/1904.03479v1
https://arxiv.org/pdf/1904.03479v1.pdf
https://github.com/mycrazycracy/tf-kaldi-speaker
true
true
false
tf
https://paperswithcode.com/paper/pymatting-a-python-library-for-alpha-matting
PyMatting: A Python Library for Alpha Matting
2003.12382
https://arxiv.org/abs/2003.12382v1
https://arxiv.org/pdf/2003.12382v1.pdf
https://github.com/pymatting/pymatting
true
true
true
paddle
https://paperswithcode.com/paper/grounded-graph-decoding-improves-1
Grounded Graph Decoding Improves Compositional Generalization in Question Answering
2111.03642
https://arxiv.org/abs/2111.03642v1
https://arxiv.org/pdf/2111.03642v1.pdf
https://github.com/gaiyu0/cfq
true
true
false
pytorch
https://paperswithcode.com/paper/bert-pre-training-of-deep-bidirectional
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
1810.04805
https://arxiv.org/abs/1810.04805v2
https://arxiv.org/pdf/1810.04805v2.pdf
https://github.com/xbtlin/All-about-Machine-Learning
false
false
true
tf
https://paperswithcode.com/paper/premvos-proposal-generation-refinement-and
PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation
1807.09190
http://arxiv.org/abs/1807.09190v2
http://arxiv.org/pdf/1807.09190v2.pdf
https://github.com/AyaLotfy/PReMVOS-trial
false
false
true
tf
https://paperswithcode.com/paper/evolvegcn-evolving-graph-convolutional
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
1902.10191
https://arxiv.org/abs/1902.10191v3
https://arxiv.org/pdf/1902.10191v3.pdf
https://github.com/IBM/EvolveGCN
true
true
true
pytorch
https://paperswithcode.com/paper/bast-bayesian-additive-regression-spanning
BAST: Bayesian Additive Regression Spanning Trees for Complex Constrained Domain
null
http://proceedings.neurips.cc/paper/2021/hash/00b76fddeaaa7d8c2c43d504b2babd8a-Abstract.html
http://proceedings.neurips.cc/paper/2021/file/00b76fddeaaa7d8c2c43d504b2babd8a-Paper.pdf
https://github.com/ztluostat/bast
true
true
false
none
https://paperswithcode.com/paper/an-end-to-end-trainable-neural-network-for
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
1507.05717
http://arxiv.org/abs/1507.05717v1
http://arxiv.org/pdf/1507.05717v1.pdf
https://github.com/SYR-Aegis/BrailleOCR
false
false
true
pytorch
https://paperswithcode.com/paper/efficient-computation-of-higher-order
Efficient computation of higher order cumulant tensors
1701.05420
http://arxiv.org/abs/1701.05420v4
http://arxiv.org/pdf/1701.05420v4.pdf
https://github.com/UnofficialJuliaMirrorSnapshots/Cumulants.jl-01e79fc4-f247-5fa3-af0e-2bd1d4cc767f
false
false
true
none
https://paperswithcode.com/paper/dense-transformer-networks
Dense Transformer Networks
1705.08881
http://arxiv.org/abs/1705.08881v2
http://arxiv.org/pdf/1705.08881v2.pdf
https://github.com/zhengyang-wang/Unet_3D
false
false
true
tf
https://paperswithcode.com/paper/formally-specifying-and-proving-operational
Formally Specifying and Proving Operational Aspects of Forensic Lucid in Isabelle
0904.3789
http://arxiv.org/abs/0904.3789v1
http://arxiv.org/pdf/0904.3789v1.pdf
https://github.com/andypitcher/Apache-FLucid
false
false
true
none
https://paperswithcode.com/paper/albert-a-lite-bert-for-self-supervised
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
1909.11942
https://arxiv.org/abs/1909.11942v6
https://arxiv.org/pdf/1909.11942v6.pdf
https://github.com/appcoreopc/berty
false
false
true
tf
https://paperswithcode.com/paper/bert-pre-training-of-deep-bidirectional
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
1810.04805
https://arxiv.org/abs/1810.04805v2
https://arxiv.org/pdf/1810.04805v2.pdf
https://github.com/appcoreopc/berty
false
false
true
tf
https://paperswithcode.com/paper/quantum-error-mitigation-by-layerwise
Quantum error mitigation by layerwise Richardson extrapolation
2402.04000
https://arxiv.org/abs/2402.04000v3
https://arxiv.org/pdf/2402.04000v3.pdf
https://github.com/unitaryfund/research
true
true
false
none
https://paperswithcode.com/paper/boosting-frank-wolfe-by-chasing-gradients
Boosting Frank-Wolfe by Chasing Gradients
2003.06369
https://arxiv.org/abs/2003.06369v2
https://arxiv.org/pdf/2003.06369v2.pdf
https://github.com/cyrillewcombettes/boostfw
true
true
true
none
https://paperswithcode.com/paper/using-agn-lightcurves-to-map-accretion-disc
Using AGN lightcurves to map accretion disc temperature fluctuations
2201.10565
https://arxiv.org/abs/2201.10565v2
https://arxiv.org/pdf/2201.10565v2.pdf
https://github.com/jackneustadt/disc-gifs
true
true
true
none
https://paperswithcode.com/paper/on-the-cobordism-class-of-the-hilbert-scheme
On the Cobordism Class of the Hilbert Scheme of a Surface
math/9904095
https://arxiv.org/abs/math/9904095v1
https://arxiv.org/pdf/math/9904095v1.pdf
https://github.com/8d1h/bott
false
false
true
none
https://paperswithcode.com/paper/retinamask-learning-to-predict-masks-improves
RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free
1901.03353
http://arxiv.org/abs/1901.03353v1
http://arxiv.org/pdf/1901.03353v1.pdf
https://github.com/latentgnn/maskrcnn-benchmark-latentgnn
false
false
true
pytorch
https://paperswithcode.com/paper/ecc-energy-constrained-deep-neural-network
ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model
1812.01803
http://arxiv.org/abs/1812.01803v3
http://arxiv.org/pdf/1812.01803v3.pdf
https://github.com/hyang1990/energy_constrained_compression
false
false
true
pytorch
https://paperswithcode.com/paper/addressing-function-approximation-error-in
Addressing Function Approximation Error in Actor-Critic Methods
1802.09477
http://arxiv.org/abs/1802.09477v3
http://arxiv.org/pdf/1802.09477v3.pdf
https://github.com/DLR-RM/stable-baselines3
false
false
false
pytorch
https://paperswithcode.com/paper/auto-encoding-variational-bayes
Auto-Encoding Variational Bayes
1312.6114
http://arxiv.org/abs/1312.6114v10
http://arxiv.org/pdf/1312.6114v10.pdf
https://github.com/DesignInformaticsLab/Morphology-Aware-Network
false
false
true
tf
https://paperswithcode.com/paper/190600621
Evolutionary Fuzzing of Android OS Vendor System Services
1906.00621
http://arxiv.org/abs/1906.00621v1
http://arxiv.org/pdf/1906.00621v1.pdf
https://github.com/dessertlab/fantastic_beasts
true
true
true
none
https://paperswithcode.com/paper/cheops-observations-of-tess-primary-mission
CHEOPS observations of TESS primary mission monotransits
2003.07620
https://arxiv.org/abs/2003.07620v1
https://arxiv.org/pdf/2003.07620v1.pdf
https://github.com/BenCooke95/CHEOPS-TESS
false
false
true
none
https://paperswithcode.com/paper/counterexample-guided-learning-of-monotonic
Counterexample-Guided Learning of Monotonic Neural Networks
2006.08852
https://arxiv.org/abs/2006.08852v1
https://arxiv.org/pdf/2006.08852v1.pdf
https://github.com/AishwaryaSivaraman/COMET
true
true
false
tf
https://paperswithcode.com/paper/srgan-training-dataset-matters
SRGAN: Training Dataset Matters
1903.09922
http://arxiv.org/abs/1903.09922v1
http://arxiv.org/pdf/1903.09922v1.pdf
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/SRGAN
false
false
false
mindspore
https://paperswithcode.com/paper/camembert-a-tasty-french-language-model
CamemBERT: a Tasty French Language Model
1911.03894
https://arxiv.org/abs/1911.03894v3
https://arxiv.org/pdf/1911.03894v3.pdf
https://github.com/hbaflast/bert-sentiment-analysis-tensorflow
false
false
true
tf
https://paperswithcode.com/paper/objects-as-points
Objects as Points
1904.07850
http://arxiv.org/abs/1904.07850v2
http://arxiv.org/pdf/1904.07850v2.pdf
https://github.com/Mind23-2/MindCode-29
false
false
true
mindspore
https://paperswithcode.com/paper/audio-text-sentiment-analysis-using-deep
Complementary Fusion of Multi-Features and Multi-Modalities in Sentiment Analysis
1904.08138
https://arxiv.org/abs/1904.08138v5
https://arxiv.org/pdf/1904.08138v5.pdf
https://github.com/robertjkeck2/EmoNet
false
false
true
none
https://paperswithcode.com/paper/seq2seq-and-joint-learning-based-unix-command
Seq2Seq and Joint Learning Based Unix Command Line Prediction System
2006.11558
https://arxiv.org/abs/2006.11558v1
https://arxiv.org/pdf/2006.11558v1.pdf
https://github.com/divyansha1115/UNIX-Command-Line-Prediction
false
false
false
none
https://paperswithcode.com/paper/imitation-learning-of-stabilizing-policies
Imitation Learning of Stabilizing Policies for Nonlinear Systems
2109.10854
https://arxiv.org/abs/2109.10854v1
https://arxiv.org/pdf/2109.10854v1.pdf
https://github.com/sebastian-east/sos-imitation-learning
true
true
true
jax
https://paperswithcode.com/paper/afn-adaptive-fusion-normalization-via-encoder
AFN: Adaptive Fusion Normalization via an Encoder-Decoder Framework
2308.03321
https://arxiv.org/abs/2308.03321v4
https://arxiv.org/pdf/2308.03321v4.pdf
https://github.com/huanranchen/ASRNorm
true
false
false
pytorch
https://paperswithcode.com/paper/targeting-sars-cov-2-with-ai-and-hpc-enabled
Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release
2006.02431
https://arxiv.org/abs/2006.02431v1
https://arxiv.org/pdf/2006.02431v1.pdf
https://github.com/globus-labs/covid-analyses
true
true
false
none
https://paperswithcode.com/paper/simple-and-scalable-predictive-uncertainty
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
1612.01474
http://arxiv.org/abs/1612.01474v3
http://arxiv.org/pdf/1612.01474v3.pdf
https://github.com/huyng/incertae
false
false
true
tf
https://paperswithcode.com/paper/tag-based-multi-span-extraction-in-reading
A Simple and Effective Model for Answering Multi-span Questions
1909.13375
https://arxiv.org/abs/1909.13375v4
https://arxiv.org/pdf/1909.13375v4.pdf
https://github.com/eladsegal/tag-based-multi-span-extraction
true
true
true
none
https://paperswithcode.com/paper/show-attend-and-tell-neural-image-caption
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
1502.03044
http://arxiv.org/abs/1502.03044v3
http://arxiv.org/pdf/1502.03044v3.pdf
https://github.com/djain454/Show-Attend-and-Tell-Neural-Image-Caption-Generation-with-Visual-Attention
false
false
true
pytorch
https://paperswithcode.com/paper/can-encrypted-dns-be-fast
Can Encrypted DNS Be Fast?
2007.06812
https://arxiv.org/abs/2007.06812v3
https://arxiv.org/pdf/2007.06812v3.pdf
https://github.com/noise-lab/dns-mba-public
true
true
false
none
https://paperswithcode.com/paper/ai-fairness-360-an-extensible-toolkit-for
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
1810.01943
http://arxiv.org/abs/1810.01943v1
http://arxiv.org/pdf/1810.01943v1.pdf
https://github.com/cesarojuliana/feature_importance_fairness
false
false
true
none
https://paperswithcode.com/paper/a-dataset-and-baselines-for-multilingual
A Dataset and Baselines for Multilingual Reply Suggestion
2106.02017
https://arxiv.org/abs/2106.02017v1
https://arxiv.org/pdf/2106.02017v1.pdf
https://github.com/zhangmozhi/mrs
true
true
true
none
https://paperswithcode.com/paper/a-simple-framework-for-contrastive-learning
A Simple Framework for Contrastive Learning of Visual Representations
2002.05709
https://arxiv.org/abs/2002.05709v3
https://arxiv.org/pdf/2002.05709v3.pdf
https://github.com/reppy4620/SimCLR4Paint
false
false
true
pytorch
https://paperswithcode.com/paper/faceboxes-a-cpu-real-time-face-detector-with
FaceBoxes: A CPU Real-time Face Detector with High Accuracy
1708.05234
http://arxiv.org/abs/1708.05234v4
http://arxiv.org/pdf/1708.05234v4.pdf
https://github.com/code-implementation1/Code3/tree/main/faceboxes
false
false
false
mindspore
https://paperswithcode.com/paper/adversarial-patch
Adversarial Patch
1712.09665
http://arxiv.org/abs/1712.09665v2
http://arxiv.org/pdf/1712.09665v2.pdf
https://github.com/zhaojb17/Adversarial_Patch_Attack
false
false
true
pytorch
https://paperswithcode.com/paper/collaborative-learning-from-distributed-data
Collaborative Learning From Distributed Data With Differentially Private Synthetic Twin Data
2308.04755
https://arxiv.org/abs/2308.04755v1
https://arxiv.org/pdf/2308.04755v1.pdf
https://github.com/dpbayes/collaborative-learning-with-dp-synthetic-twin-data
true
true
false
jax
https://paperswithcode.com/paper/deep-predictive-coding-networks-for-video
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
1605.08104
http://arxiv.org/abs/1605.08104v5
http://arxiv.org/pdf/1605.08104v5.pdf
https://github.com/ramyamounir/PredNet
false
false
true
tf
https://paperswithcode.com/paper/the-mcc-f1-curve-a-performance-evaluation
The MCC-F1 curve: a performance evaluation technique for binary classification
2006.11278
https://arxiv.org/abs/2006.11278v1
https://arxiv.org/pdf/2006.11278v1.pdf
https://github.com/arthurcgusmao/py-mcc-f1
false
false
true
none
https://paperswithcode.com/paper/multi-level-wavelet-convolutional-neural
Multi-level Wavelet Convolutional Neural Networks
1907.03128
https://arxiv.org/abs/1907.03128v1
https://arxiv.org/pdf/1907.03128v1.pdf
https://github.com/AureliePeng/Keras-WaveletTransform
false
false
true
none
https://paperswithcode.com/paper/dueling-network-architectures-for-deep
Dueling Network Architectures for Deep Reinforcement Learning
1511.06581
http://arxiv.org/abs/1511.06581v3
http://arxiv.org/pdf/1511.06581v3.pdf
https://github.com/ku2482/sac-discrete.pytorch
false
false
true
pytorch
https://paperswithcode.com/paper/fine-tuning-by-curriculum-learning-for-non
Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation
1911.08717
https://arxiv.org/abs/1911.08717v2
https://arxiv.org/pdf/1911.08717v2.pdf
https://github.com/josephch405/curriculum-nmt
false
false
true
pytorch
https://paperswithcode.com/paper/mockfog-2-0-automated-execution-of-fog
MockFog 2.0: Automated Execution of Fog Application Experiments in the Cloud
2009.10579
https://arxiv.org/abs/2009.10579v2
https://arxiv.org/pdf/2009.10579v2.pdf
https://github.com/OpenFogStack/MockFog2
true
true
false
none
https://paperswithcode.com/paper/simple-online-and-realtime-tracking-with-a
Simple Online and Realtime Tracking with a Deep Association Metric
1703.07402
http://arxiv.org/abs/1703.07402v1
http://arxiv.org/pdf/1703.07402v1.pdf
https://github.com/kshitij1489/object-tracking
false
false
true
tf
https://paperswithcode.com/paper/attentive-weights-generation-for-few-shot-1
Attentive Weights Generation for Few Shot Learning via Information Maximization
null
http://openaccess.thecvf.com/content_CVPR_2020/html/Guo_Attentive_Weights_Generation_for_Few_Shot_Learning_via_Information_Maximization_CVPR_2020_paper.html
http://openaccess.thecvf.com/content_CVPR_2020/papers/Guo_Attentive_Weights_Generation_for_Few_Shot_Learning_via_Information_Maximization_CVPR_2020_paper.pdf
https://github.com/Yiluan/AWGIM
true
true
false
tf
https://paperswithcode.com/paper/very-deep-convolutional-networks-for-large
Very Deep Convolutional Networks for Large-Scale Image Recognition
1409.1556
http://arxiv.org/abs/1409.1556v6
http://arxiv.org/pdf/1409.1556v6.pdf
https://github.com/cryu854/ArbitraryStyle-tfjs
false
false
true
tf
https://paperswithcode.com/paper/190600363
Does It Make Sense? And Why? A Pilot Study for Sense Making and Explanation
1906.00363
https://arxiv.org/abs/1906.00363v2
https://arxiv.org/pdf/1906.00363v2.pdf
https://github.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation
false
false
true
none