rishabhk108 / OptimizationDemosLinks
Some simple demos I use in my optimization in ML course. Includes implementations of ML loss functions (Logistic Loss, SVM Loss, ..) and optimization algorithms (gradient descent, accelerated variants, conjugate GD, etc.)
☆13Updated 4 years ago
Alternatives and similar repositories for OptimizationDemos
Users that are interested in OptimizationDemos are comparing it to the libraries listed below
Sorting:
- Explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective (https://arxiv.org/abs/1912.02757) by Stanislav Fort, Huiyi …☆65Updated 5 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- This repository holds code and other relevant files for the NeurIPS 2022 tutorial: Foundational Robustness of Foundation Models.☆72Updated 2 years ago
- ModelDiff: A Framework for Comparing Learning Algorithms☆59Updated 2 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆89Updated last year
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 3 months ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- Self-Explaining Neural Networks☆42Updated 5 years ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆130Updated 3 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆90Updated last year
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆40Updated 4 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated 3 months ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆54Updated 3 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- This repository contains the code of the distribution shift framework presented in A Fine-Grained Analysis on Distribution Shift (Wiles e…☆83Updated 2 months ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Code for "Generative causal explanations of black-box classifiers"☆35Updated 4 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- A library for uncertainty quantification based on PyTorch☆122Updated 3 years ago
- 👋 Code for the paper: "Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis" (NeurIPS 2021)☆30Updated 3 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆85Updated last year
- Neural Ensemble Search for Uncertainty Estimation and Dataset Shift☆33Updated last year
- ☆54Updated last year
- Last-layer Laplace approximation code examples☆84Updated 3 years ago
- The official repository for our paper "Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks". We…☆46Updated last year
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- Codebase for Learning Invariances in Neural Networks☆95Updated 2 years ago