uvadlc / uvadlc_practicals_2020Links
☆22Updated 5 years ago
Alternatives and similar repositories for uvadlc_practicals_2020
Users that are interested in uvadlc_practicals_2020 are comparing it to the libraries listed below
Sorting:
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆130Updated 3 years ago
- MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space☆41Updated 4 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆90Updated last year
- ☆19Updated 3 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆87Updated last year
- Code repository of the paper "CKConv: Continuous Kernel Convolution For Sequential Data" published at ICLR 2022. https://arxiv.org/abs/21…☆124Updated 3 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆37Updated 3 years ago
- Last-layer Laplace approximation code examples☆83Updated 4 years ago
- Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"☆81Updated 3 years ago
- Repository with all material for SMILES, the Summer School of Machine Learning at Skoltech, taking place from the 16th to the 21st of Aug…☆55Updated 5 years ago
- ☆45Updated 5 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated last year
- Notebook for comprehensive analysis of authors, organizations, and countries of ICML 2020 papers.☆56Updated 5 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 4 years ago
- ☆111Updated 3 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆43Updated 3 years ago
- Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"☆37Updated 2 years ago
- Explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective (https://arxiv.org/abs/1912.02757) by Stanislav Fort, Huiyi …☆66Updated 5 years ago
- ☆38Updated 4 years ago
- ☆54Updated last year
- ☆37Updated 3 years ago
- ☆16Updated 3 years ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 4 years ago
- https://cs330.stanford.edu/☆62Updated 2 years ago
- Framework code with wandb, checkpointing, logging, configs, experimental protocols. Useful for fine-tuning models or training from scratc…☆152Updated 2 years ago
- Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding☆73Updated 4 years ago
- Active and Sample-Efficient Model Evaluation☆26Updated 7 months ago
- Neural Networks and Deep Learning, NUS CS5242, 2021☆191Updated 4 years ago
- Collection of snippets for PyTorch users☆25Updated 3 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆37Updated 3 years ago