On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification
☆21Apr 1, 2022Updated 3 years ago
Alternatives and similar repositories for understanding-bayesian-classification
Users that are interested in understanding-bayesian-classification are comparing it to the libraries listed below
Sorting:
- A list of all papers related to anomaly detection in NeurIPS 2020.☆10Jan 13, 2021Updated 5 years ago
- NOMU: Neural Optimization-based Model Uncertainty☆10Feb 17, 2023Updated 3 years ago
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆14Aug 19, 2022Updated 3 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆92May 14, 2024Updated last year
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆36Jun 16, 2022Updated 3 years ago
- ☆16Oct 8, 2021Updated 4 years ago
- ☆15Sep 11, 2022Updated 3 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆16Dec 30, 2022Updated 3 years ago
- Code to reproduce results from "Invertible generative models for inverse problems: mitigating representation error and dataset bias"☆21Jul 9, 2020Updated 5 years ago
- ☆18Apr 1, 2020Updated 5 years ago
- Bayesian Optimization with Density-Ratio Estimation☆24Dec 26, 2022Updated 3 years ago
- ☆22May 16, 2022Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆22Dec 30, 2021Updated 4 years ago
- Random feature latent variable models in Python☆23Jul 23, 2023Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆60Jul 1, 2021Updated 4 years ago
- ☆29Apr 27, 2023Updated 2 years ago
- Code for Understanding and Mitigating Exploding Inverses in Invertible Neural Networks (AISTATS 2021) http://arxiv.org/abs/2006.09347☆30Aug 29, 2020Updated 5 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆25Dec 19, 2022Updated 3 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Jul 4, 2024Updated last year
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆40Sep 18, 2025Updated 5 months ago
- Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization☆42Sep 7, 2021Updated 4 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆39Jun 21, 2022Updated 3 years ago
- spatial transformer for 3d point clouds☆32Dec 16, 2021Updated 4 years ago
- Code related to the paper "On instabilities of deep learning in image reconstruction - Does AI come at a cost?"☆36May 18, 2025Updated 9 months ago
- Introduction to Machine Learning using scikit-learn and PyTorch☆10Sep 26, 2019Updated 6 years ago
- Code for the paper "Semi-Conditional Normalizing Flows for Semi-Supervised Learning"☆11Mar 30, 2020Updated 5 years ago
- ☆11May 16, 2025Updated 9 months ago
- ☆11Jun 18, 2023Updated 2 years ago
- ☆42Sep 20, 2022Updated 3 years ago
- on-policy optimization baselines for deep reinforcement learning☆32Apr 3, 2020Updated 5 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆44Nov 25, 2024Updated last year
- ☆10Jan 28, 2024Updated 2 years ago
- ☆12Oct 24, 2023Updated 2 years ago
- TMI 2023: FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image Recognition☆11Mar 19, 2024Updated last year
- ☆12Sep 24, 2024Updated last year
- Code for "Thinking Forward: Memory-Efficient Federated Finetuning of Language Models" (NeurIPS 2024). Spry is a federated learning al…☆12Oct 8, 2024Updated last year
- Find ground breaking 3D point cloud analysis papers☆13Jul 28, 2020Updated 5 years ago
- ☆11Dec 19, 2023Updated 2 years ago
- ☆13Jul 25, 2025Updated 7 months ago