claudia-viaro / Wdss-UCLdss_research
☆12Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for Wdss-UCLdss_research
- Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆129Updated last year
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆19Updated 2 years ago
- Density Ratio Estimation via Infinitesimal Classification (AISTATS 2022 Oral)☆17Updated 2 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆88Updated 6 months ago
- ☆22Updated 3 years ago
- Jupyter notebooks on inference, regression and classification for MPhil students☆45Updated last month
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆202Updated 5 months ago
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆49Updated last year
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆186Updated 2 weeks ago
- Materials of the Nordic Probabilistic AI School 2022.☆171Updated 2 years ago
- An official repository for a VAE tutorial of Probabilistic Modelling and Reasoning (2023/2024) - a University of Edinburgh master's cours…☆8Updated 10 months ago
- Dataset repository for the 2024 paper "The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology" by Juan L. Gamella, Jo…☆23Updated this week
- Regression datasets from the UCI repository with standardized test-train splits.☆36Updated 2 years ago
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆189Updated 7 months ago
- Repo for the Tutorials of Day1-Day2 of the Nordic Probabilistic AI School 2023☆17Updated last year
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆159Updated 5 months ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆21Updated 2 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 9 months ago
- Materials of the Nordic Probabilistic AI School 2023.☆86Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆53Updated 2 months ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆46Updated last year
- ☆38Updated this week
- Normalizing Flows with a resampled base distribution☆44Updated 2 years ago
- Agustinus' very opiniated publication-ready plotting library☆57Updated 2 months ago
- A Python toolbox for conformal prediction research on deep learning models, using PyTorch.☆230Updated this week
- Neural Tangent Kernel Papers☆92Updated 8 months ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆47Updated 4 years ago
- ☆41Updated 8 months ago
- MIGSAA Project 2 - Langevin Monte Carlo Algorithms☆12Updated last year
- A framework for composing Neural Processes in Python☆78Updated 5 months ago