Alternatives and similar repositories for IntegratedGradientsPytorch

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

• chenw20 / SGPA
  Example code of Sparse Gaussian Process Attention (ICLR 2023)
  ☆26Updated 2 months ago
• zhougroup / BAM
  Bayesian Attention Modules
  ☆35Updated 4 years ago
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆44Updated 11 months ago
• LJSthu / HRM
  The code for the paper 'Heterogeneous Risk Minimization' of ICML2021.
  ☆25Updated 4 years ago
• clear-nus / NCDSSM
  PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularl…
  ☆25Updated 2 years ago
• weitianxin / awesome-distribution-shift
  A curated list of papers and resources about the distribution shift in machine learning.
  ☆123Updated 2 years ago
• namkoong-lab / whyshift
  A python package providing a benchmark with various specified distribution shift patterns.
  ☆58Updated last year
• xu-ji / information-bottleneck
  Deep Learning & Information Bottleneck
  ☆62Updated 2 years ago
• Junghwan-brian / SDE-Net
  implementations sde-net
  ☆14Updated 4 years ago
• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆78Updated 3 years ago
• burklight / nonlinear-IB-PyTorch
  Pytorch Implementation of the Nonlinear Information Bottleneck
  ☆40Updated last year
• thudzj / NeuralEigenFunction
  ☆17Updated 3 years ago
• kimjeyoung / SNGP-BERT-Pytorch
  This is reimplementation of "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" in Pyt…
  ☆52Updated 4 years ago
• changliu00 / causal-semantic-generative-model
  Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …
  ☆76Updated 3 years ago
• inouye-lab / ShapleyExplanationNetworks
  Implementation of the paper "Shapley Explanation Networks"
  ☆88Updated 4 years ago
• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆29Updated last year
• LFhase / PAIR
  [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
  ☆53Updated last year
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆51Updated 4 years ago
• ruchtem / cosmos
  This is the official implementation for COSMOS: a method to learn Pareto fronts that scales to large datasets and deep models.
  ☆39Updated 4 years ago
• Shen-Lab / Bayesian-L2O
  [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…
  ☆14Updated 3 years ago
• ElisaNguyen / bayesian-tda
  Code for NeurIPS'23 paper "A Bayesian Approach To Analysing Training Data Attribution In Deep Learning"
  ☆17Updated last year
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆60Updated last year
• patrickrchao / DiffusionBasedCausalModels
  ☆28Updated 7 months ago
• huaxiuyao / Wild-Time
  Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)
  ☆68Updated 2 years ago
• Rose-STL-Lab / AutoODE-DSL
  ☆13Updated 4 years ago
• automl / is_mamba_capable_of_icl
  ☆18Updated last year
• layer6ai-labs / WinIT
  Code for the ICLR'23 paper "Temporal Dependencies in Feature Importance for Time Series Prediction"
  ☆26Updated 2 years ago
• MangoKiller / SimOAR_OAR
  ☆11Updated 2 years ago
• facebookresearch / neural_stpp
  Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domain…
  ☆105Updated 3 years ago