Alternatives and similar repositories for GBDT-NAS

Users that are interested in GBDT-NAS are comparing it to the libraries listed below

• Torment123 / DFS
  ☆15Updated 5 years ago
• angelajiang / SelectiveBackprop
  SelectiveBackprop accelerates training by dynamically prioritizing useful examples with high loss
  ☆32Updated 5 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
• gatech-sysml / CompOFA
  [ICLR 2021] CompOFA: Compound Once-For-All Networks For Faster Multi-Platform Deployment
  ☆24Updated 2 years ago
• Cerebras / online-normalization
  Online Normalization for Training Neural Networks (Companion Repository)
  ☆82Updated 4 years ago
• houlu369 / Normalized-Quantized-LSTM
  Implementation of NeurIPS 2019 paper "Normalization Helps Training of Quantized LSTM"
  ☆31Updated 10 months ago
• Separius / CudaRelativeAttention
  custom cuda kernel for {2, 3}d relative attention with pytorch wrapper
  ☆43Updated 5 years ago
• haolibai / APS-channel-search
  Revisiting Parameter Sharing for Automatic Neural Channel Number Search, NeurIPS 2020
  ☆21Updated 4 years ago
• eric8607242 / SGNAS
  [CVPR 2021] Searching by Generating: Flexible and Efficient One-Shot NAS with Architecture Generator
  ☆38Updated 3 years ago
• stevenygd / SWALP
  Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".
  ☆62Updated 6 years ago
• ofsoundof / learning_filter_basis
  Pytorch implemenation of "Learning Filter Basis for Convolutional Neural Network Compression" ICCV2019
  ☆18Updated 3 years ago
• xiangning-chen / DrNAS
  Code for our ICLR'2021 paper "DrNAS: Dirichlet Neural Architecture Search"
  ☆44Updated 4 years ago
• Jangho-Kim / PSG-pytorch
  Position-based Scaled Gradient for Model Quantization and Pruning Code (NeurIPS 2020)
  ☆26Updated 4 years ago
• csyhhu / MetaQuant
  Codes for Accepted Paper : "MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization" in NeurIPS 2019
  ☆54Updated 5 years ago
• skhu101 / GM-NAS
  Code for our ICLR'2022 paper "Generalizing Few-Shot NAS with Gradient Matching"
  ☆22Updated 2 years ago
• renqianluo / SemiNAS
  ☆26Updated 4 years ago
• xiaomi-automl / MixPath
  MixPath: A Unified Approach for One-shot Neural Architecture Search
  ☆29Updated 4 years ago
• LaVieEnRoseSMZ / OQA
  ☆28Updated 4 years ago
• NingMiao / InteL-VAEs
  Codes for paper <InteL-VAEs: Adding Inductive Biases to VariationalAuto-Encoders via Intermediary Latents>.
  ☆19Updated 3 years ago
• facebookresearch / AttentiveNAS
  code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"
  ☆104Updated 3 years ago
• SamsungLabs / nb-asr
  ☆27Updated 2 years ago
• xiaomi-automl / NoisyDARTS
  Noisy Differentiable Architecture Search
  ☆23Updated 3 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
• HayeonLee / MetaD2A
  Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)
  ☆64Updated 10 months ago
• ziplab / SAQ
  This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
  ☆43Updated 3 years ago
• 1adrianb / binary-nas
  ☆35Updated 5 years ago
• YuchenJin / autolrs
  Automatic learning-rate scheduler
  ☆45Updated 4 years ago
• houlu369 / Loss-aware-weight-quantization
  Implementation of ICLR 2018 paper "Loss-aware Weight Quantization of Deep Networks"
  ☆26Updated 5 years ago
• houlu369 / Loss-aware-Binarization
  Implementation of ICLR 2017 paper "Loss-aware Binarization of Deep Networks"
  ☆18Updated 6 years ago
• DingXiaoH / GSM-SGD
  Global Sparse Momentum SGD for pruning very deep neural networks
  ☆44Updated 2 years ago