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

• chingyaoc / TMD
  NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
  ☆36Updated last year
• JeanKaddour / SIN
  Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
  ☆42Updated 2 years ago
• LARS-research / TabGNN
  ☆48Updated 3 years ago
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆22Updated 4 years ago
• sxjscience / automl_multimodal_benchmark
  Repository for Multimodal AutoML Benchmark
  ☆64Updated 3 years ago
• flyingtango / DiGCL
  The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
  ☆36Updated 3 years ago
• ahujak / IB-IRM
  ☆30Updated 3 years ago
• StatsDLMathsRecomSys / Self-attention-with-Functional-Time-Representation-Learning
  ☆50Updated last year
• epfl-lts2 / GraphMining-TheWebConf2021
  ☆14Updated 3 years ago
• moorecsys / moorecsys.github.io
  Tutorial on Multi-Objective Recommender Systems @ KDD 2021
  ☆19Updated 2 years ago
• Daftstone / CIMI
  ☆26Updated last year
• carolinlawrence / gradient-rollback
  Code for gradient rollback, which explains predictions of neural matrix factorization models, as for example used for knowledge base comp…
  ☆21Updated 3 years ago
• DeepGraphLearning / SPN
  ☆29Updated 2 years ago
• xiangwang1223 / reinforced_causal_explainer
  Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
  ☆33Updated 2 years ago
• DAMO-DI-ML / KDD2022-Tutorial-Time-Series
  KDD'22 Tutorial: Robust Time Series Analysis and Applications An Industrial Perspective
  ☆31Updated last year
• YoungseogChung / calibrated-quantile-uq
  Training quantile models
  ☆42Updated 2 months ago
• ninghaohello / Interpretation2Adversary
  Adversarial learning by utilizing model interpretation
  ☆10Updated 6 years ago
• ondrejbohdal / meta-calibration
  Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"
  ☆33Updated last year
• thudzj / NEigenmaps
  ☆11Updated 11 months ago
• cyber-meow / PUbiasedN
  PyTorch implementation for the paper Classification from Positive, Unlabeled and Biased Negative Data.
  ☆19Updated last year
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆21Updated 2 years ago
• dlranking / dlrr
  DeepSearchRelevanceRanking-KDD2022-Tutorial
  ☆15Updated 2 years ago
• yandex-research / tabgraphs
  A benchmark of meaningful graph datasets with tabular node features
  ☆12Updated 3 weeks ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 4 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• sharpenb / Uncertainty-Event-Prediction
  Uncertainty on Asynchronous Time Event Prediction (Spotlight, Neurips 2019)
  ☆18Updated 4 years ago
• zetayue / CPA
  Source code for "Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation" (IJCAI 2020)
  ☆17Updated 6 months ago
• hongyuanmei / tpp-short-course
  A short course on temporal point process and modeling irregular time series
  ☆21Updated 4 years ago
• mkrzywda / GraphTransformers
  Sandbox to analysis and benchmarking Graph Transformer Neural Networks
  ☆33Updated 2 years ago
• yang-han / P-reg
  Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)
  ☆34Updated 3 years ago