bknyaz

bknyaz's Stars

• facebookresearch/nevergrad

  A Python toolbox for performing gradient-free optimization

  Language:Python4k58264355

• microsoft/Graphormer

  Graphormer is a general-purpose deep learning backbone for molecular modeling.

  Language:Python2.1k31154337

• mit-han-lab/once-for-all

  [ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

  Language:Python1.9k5375333

• facebookresearch/ppuda

  Code for Parameter Prediction for Unseen Deep Architectures (NeurIPS 2021)

  Language:Python48420460

• microsoft/scene_graph_benchmark

  image scene graph generation benchmark

  Language:Python390139586

• chenxin061/pdarts

  Codes for our paper "Progressive Differentiable Architecture Search:Bridging the Depth Gap between Search and Evaluation"

  Language:Python36074183

• linkedin/dagli

  Framework for defining machine learning models, including feature generation and transformations, as directed acyclic graphs (DAGs).

  Language:Java354201440

• google-research/task_adaptation

  Language:Python311161535

• facebookresearch/amortized-optimization-tutorial

  Tutorial on amortized optimization for learning to optimize over continuous domains

  Language:TeX2369012

• jxbz/agd

  Automatic gradient descent

  Language:TeX2064313

• xiaomi-automl/FairDARTS

  Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search

  Language:Python1738035

• DevinKreuzer/SAN

  Language:Python1497530

• YiwuZhong/SGG_from_NLS

  [ICCV 2021] Official code for "Learning to Generate Scene Graph from Natural Language Supervision"

  Language:Jupyter Notebook10061010

• mistyreed63849/Graph-LLM

  GraphLLM: Boosting Graph Reasoning Ability of Large Language Model

  Language:Python983610

• mods333/energy-based-scene-graph

  Code release for Energy-Based Learning for Scene Graph Genertaion

  Language:Jupyter Notebook924911

• VITA-Group/LiGO

  [ICLR 2023] "Learning to Grow Pretrained Models for Efficient Transformer Training" by Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen, Philip Greengard, Leonid Karlinsky, Rogerio Feris, David Cox, Zhangyang Wang, Yoon Kim

  Language:Python822629

• mkofinas/neural-graphs

  Official source code for "Graph Neural Networks for Learning Equivariant Representations of Neural Networks". In ICLR 2024 (oral).

  Language:Python70335

• ModelZoos/ModelZooDataset

  Model Zoos published at the NeurIPS 2022 Dataset & Benchmark track: "Model Zoos: A Dataset of Diverse Populations of Neural Network Models"

  Language:Python54431

• uoguelph-mlrg/GenerativeLEGO

  Code implementation for the paper "Building LEGO Using Deep Generative Models of Graphs"

  Language:Python50408

• layer6ai-labs/SGG-Seq2Seq

  Code for the ICCV'21 paper "Context-aware Scene Graph Generation with Seq2Seq Transformers"

  Language:Python44594

• jrwnter/pigvae

  Implementation of the Paper "Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning" by Robin Winter, Frank Noe and Djork-Arne Clevert.

  Language:Python423612

• uoguelph-mlrg/GGM-metrics

  Official repository for the paper "On Evaluation Metrics for Graph Generative Models"

  Language:Jupyter Notebook26213

• Blackzxy/LoGAH

  Language:Python21231

• SamsungSAILMontreal/AnyMolGenCritic

  Language:Python20301

• HSG-AIML/NeurIPS_2021-Weight_Space_Learning

  Code Repository for the NeurIPS 2021 paper: "Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction".

  Language:Python17412

• POSTECH-CVLab/Brick-by-Brick

  Official repository of Brick-by-Brick, presented at NeurIPS-2021

  Language:Python14701

• YichaoLu/Science4cast2021

  Language:Python6100

• amoudgl/distributed-dtp

  Distributed implementation of our proposed DTP algorithm parallelizing feedback weight training across GPUs (ICML 2022)

  Language:Python4311

• lefameuxbeding/learned_aggregation

  Language:Python4402

• VectorInstitute/ppuda

  Code for Parameter Prediction for Unseen Deep Architectures (NeurIPS 2021)

  Language:Python110