sscardapane / hydra-tutorial

Related projects: ⓘ

• ganguli-lab / degrees-of-freedom
  ☆35Updated 2 years ago
• fsschneider / cockpit-experiments
  Experiments for the NeurIPS 2021 paper "Cockpit: A Practical Debugging Tool for the Training of Deep Neural Networks"
  ☆13Updated 2 years ago
• Lightning-Universe / Research-template
  Quickest way to share everything about your research within a single app
  ☆37Updated 2 months ago
• hadyelsahar / EBM-visualizations
  notebooks of cool EBM visualizations
  ☆16Updated 3 years ago
• ericmjl / score-models
  In which I learn about score functions and how they can be used to generate data.
  ☆14Updated 5 months ago
• ml-jku / quam
  Quantification of Uncertainty with Adversarial Models
  ☆27Updated last year
• stanfordmlgroup / disentanglement
  Official repository for our ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology
  ☆36Updated 3 years ago
• ahthie7u / cockpit
  Code for the anonymous submission "Cockpit: A Practical Debugging Tool for Training Deep Neural Networks"
  ☆31Updated 3 years ago
• marharyta-aleksandrova / conformal-learning
  Code related to different aspects of conformal learning
  ☆15Updated 11 months ago
• vtopt / qnstop
  Quasi-Newton Algorithm for Stochastic Optimization
  ☆10Updated 2 years ago
• nickfrosst / neural_additive_models
  stand alone Neural Additive Models, forked from google-reasearch for easy import to colab
  ☆26Updated 3 years ago
• distillpub / post--grand-tour
  ☆28Updated last year
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆21Updated last year
• mhlr / awesome-jax
  List of awesome JAX resources
  ☆12Updated last year
• craffel / jax-tutorial
  A tutorial on JAX (https://github.com/google/jax/)
  ☆45Updated 5 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆21Updated 11 months ago
• siboehm / NormalizingFlowNetwork
  Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982
  ☆21Updated 3 years ago
• samuelstanton / conformal-bayesopt
  Bayesian optimization with conformal coverage guarantees
  ☆26Updated last year
• lvwerra / deep-math
  Implementation of "Analysing Mathematical Reasoning Abilities of Neural Models"
  ☆29Updated last year
• yannadani / cbed
  Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.
  ☆19Updated last year
• microprediction / optimizer-elo-ratings
  Assigns Elo Ratings to Python Global Optimizers
  ☆22Updated 5 months ago
• probml / bandits
  Bayesian Bandits
  ☆64Updated last year
• rasbt / srgan-lightning-blog
  Sharing Deep Learning Research Models with Lightning Part 1: Building A Super Resolution App
  ☆14Updated 2 years ago
• pyro-ppl / sandbox
  Pyro models and misc examples.
  ☆19Updated 3 years ago
• jmkuebler / auto-tst
  AutoML Two-Sample Test
  ☆18Updated 2 years ago
• lucidrains / hopular-pytorch
  ☆21Updated this week
• jmtomczak / git_flow
  General Invertible Transformations for Flow-based Generative Models
  ☆17Updated 3 years ago
• vitalab / neuralteleportation
  Isomorphisms of quiver representations applied to neural networks.
  ☆15Updated last month
• edwardjhu / improved_wasserstein
  Code for our ICLR Trustworthy ML 2020 workshop paper "Improved Image Wasserstein Attacks and Defenses"
  ☆13Updated 4 years ago
• fastai / fastpy
  An easy way to start a python programming environment using GitHub Codespaces.
  ☆15Updated 4 years ago