Alternatives and similar repositories for vs_gae:

Users that are interested in vs_gae are comparing it to the libraries listed below

• naszilla / nas-encodings
  Encodings for neural architecture search
  ☆29Updated 4 years ago
• ashaw596 / meta_architecture_search
  ☆21Updated 5 years ago
• hongyanz / TRADES-smoothing
  [JMLR] TRADES + random smoothing for certifiable robustness
  ☆14Updated 4 years ago
• AIoT-MLSys-Lab / CATE
  [ICML 2021 Oral] "CATE: Computation-aware Neural Architecture Encoding with Transformers" by Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang
  ☆19Updated 3 years ago
• tianyizhou / DoCL
  Paper and Code for "Curriculum Learning by Optimizing Learning Dynamics" (AISTATS 2021)
  ☆19Updated 3 years ago
• 962086838 / code-for-Asymmetric-Valley
  This repo contains the code used for NeurIPS 2019 paper "Asymmetric Valleys: Beyond Sharp and Flat Local Minima".
  ☆14Updated 5 years ago
• AIoT-MLSys-Lab / arch2vec
  [NeurIPS 2020] "Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?" by Shen Yan, Yu Zheng, Wei Ao, X…
  ☆49Updated 4 years ago
• henrygouk / mars-finetuning
  ☆19Updated 4 years ago
• VITA-Group / triple-wins
  [ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“
  ☆24Updated 3 years ago
• minhtannguyen / SRSGD
  Code base for SRSGD.
  ☆28Updated 5 years ago
• huangleiBuaa / IterNorm
  This project is the Torch implementation of our accepted CVPR 2019 paper, Iterative Normalization: Beyond Standardization towards Effic…
  ☆25Updated 4 years ago
• xiangning-chen / DrNAS
  Code for our ICLR'2021 paper "DrNAS: Dirichlet Neural Architecture Search"
  ☆44Updated 4 years ago
• XinbangZhang / DATA-NAS
  Codes for DATA: Differentiable ArchiTecture Approximation.
  ☆11Updated 3 years ago
• k9k2 / qSGD
  SGD and Ordered SGD codes for deep learning, SVM, and logistic regression
  ☆35Updated 4 years ago
• szkocot / Adapting-Auxiliary-Losses-Using-Gradient-Similarity
  Implementation "Adapting Auxiliary Losses Using Gradient Similarity" article
  ☆32Updated 6 years ago
• VITA-Group / WeakNAS
  [NeurIPS 2021] “Stronger NAS with Weaker Predictors“, Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang W…
  ☆27Updated 2 years ago
• VITA-Group / Once-for-All-Adversarial-Training
  [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…
  ☆44Updated 3 years ago
• realityengines / local_search
  Local search for NAS
  ☆18Updated 4 years ago
• VITA-Group / TEGNAS
  "Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics" by Wuyang Chen, Xinyu Gong, Yu…
  ☆26Updated last year
• aoiang / few-shot-NAS
  ☆40Updated last year
• xinshi-chen / l2stop
  Learning To Stop While Learning To Predict
  ☆34Updated 2 years ago
• shuyao95 / Understanding-NAS
  Codes for Understanding Architectures Learnt by Cell-based Neural Architecture Search
  ☆27Updated 5 years ago
• eladhoffer / norm_matters
  ☆23Updated 6 years ago
• xjtushujun / Meta-weight-net_class-imbalance
  NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for class imbalance).
  ☆33Updated 5 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆28Updated 6 years ago
• huangleiBuaa / OthogonalWN
  This project is the Torch implementation of our accepted AAAI 2018 paper : orthogonal weight normalization method for solving orthogonali…
  ☆57Updated 5 years ago
• xingchenwan / nasbowl
  [ICLR '21] Interpretable Neural Architecture Search using Bayesian Optimisation with Weisfiler-Lehman Kernel (NAS-BOWL)
  ☆24Updated 3 years ago
• yuhuixu1993 / Trained-Rank-Pruning
  Pytorch implementation of TRP
  ☆45Updated 4 years ago
• erogol / Net2Net
  Net2Net implementation on PyTorch for any possible vision layers.
  ☆38Updated 7 years ago
• wenwei202 / smoothout
  SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning
  ☆23Updated 6 years ago