Personalized Federated Learning via Variational Bayesian Inference [ICML 2022]
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Updated
Jul 31, 2022 - Python
Personalized Federated Learning via Variational Bayesian Inference [ICML 2022]
This is a PyTorch implementation of a Bayesian Convolutional Neural Network (BCNN) for Semantic Scene Completion on the SUNCG dataset. Given a depth image the network outputs a semantic segmentation and entropy score in 3D voxel format.
Tutorials in various concepts related to deep learning
Deep Modeling of Strong Gravitational Time Delay Lenses for Bayesian Inference of the Hubble Constant
Bayesian deep learning experiments
[NeurIPS'23] Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations
An experimental Python package for learning Bayesian Neural Network.
[NeurIPS 2023] Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing
Model which can predict COVID-19 positive case from axial lung CT-scan images.
(Forked Version) Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"
My attempt at SAiDL's 2022 Spring Assignment
Task in belong laboratory (related: https://github.com/chiru1221/LabStudyTask2020)
Binary and multiclass comparison of Bayesian Neural Network and Simple Neural Network
Deep Generative Bayesian Network
AI Repository
Bayesian neural networks in PyTorch
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