Alternatives and similar repositories for kdd-2022-multimodal-automl-tutorial

Users that are interested in kdd-2022-multimodal-automl-tutorial are comparing it to the libraries listed below

• JeanKaddour / SIN
  Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
  ☆42Updated 3 years ago
• mwcvitkovic / Supervised-Learning-on-Relational-Databases-with-GNNs
  Code to reproduce the results in the paper Supervised Learning on Relational Databases with Graph Neural Networks.
  ☆62Updated 5 years ago
• lightlightdyy / Deep-Learning-and-Causal-Inference
  ☆29Updated 6 years ago
• thudzj / NEigenmaps
  ☆12Updated last year
• epfl-lts2 / GraphMining-TheWebConf2021
  ☆14Updated 4 years ago
• LARS-research / TabGNN
  ☆50Updated 3 years ago
• yang-han / P-reg
  Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)
  ☆34Updated 4 years ago
• sxjscience / automl_multimodal_benchmark
  Repository for Multimodal AutoML Benchmark
  ☆66Updated 3 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• berkeley-reclab / RecLab
  ☆66Updated 2 years ago
• ahujak / IB-IRM
  ☆30Updated 3 years ago
• chingyaoc / TMD
  NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
  ☆36Updated last year
• ninghaohello / Interpretation2Adversary
  Adversarial learning by utilizing model interpretation
  ☆10Updated 6 years ago
• moorecsys / moorecsys.github.io
  Tutorial on Multi-Objective Recommender Systems @ KDD 2021
  ☆19Updated 2 years ago
• fairkmeans / Fair-K-Means-Clustering
  Code of the paper Fair k-Means Clustering
  ☆13Updated 3 years ago
• qema / bidyn
  ☆21Updated 3 years ago
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆23Updated 4 years ago
• HazyResearch / mandoline
  (ICML 2021) Mandoline: Model Evaluation under Distribution Shift
  ☆31Updated 3 years ago
• FilippoMB / Total-variation-graph-neural-networks
  Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.
  ☆20Updated 2 months ago
• ritaranx / CACHE
  [ML4H 2022] This is the code for our paper `Counterfactual and Factual Reasoning over Hypergraphs for Interpretable Clinical Predictions …
  ☆25Updated last year
• cyber-meow / PUbiasedN
  PyTorch implementation for the paper Classification from Positive, Unlabeled and Biased Negative Data.
  ☆19Updated last year
• flyingtango / DiGCL
  The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
  ☆35Updated 3 years ago
• StatsDLMathsRecomSys / Self-attention-with-Functional-Time-Representation-Learning
  ☆50Updated 2 years ago
• carolinlawrence / gradient-rollback
  Code for gradient rollback, which explains predictions of neural matrix factorization models, as for example used for knowledge base comp…
  ☆21Updated 4 years ago
• lethaiq / GRACE_KDD20
  GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon …
  ☆21Updated 4 years ago
• delta2323 / gnn-asymptotics
  Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.
  ☆30Updated 5 years ago
• moranbel / tdGraphEmbed
  ☆21Updated last year
• GentleZhu / EGI
  Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')
  ☆23Updated 3 years ago
• snap-stanford / crust
  [NeurIPS 2020] Coresets for Robust Training of Neural Networks against Noisy Labels
  ☆34Updated 4 years ago
• GentleZhu / Shift-Robust-GNNs
  "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')
  ☆48Updated 3 years ago