Framework for integrating prior knowledge into trajectory prediction models for autonomous driving via Bayesian continual learning.
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Updated
Nov 28, 2022 - Python
Framework for integrating prior knowledge into trajectory prediction models for autonomous driving via Bayesian continual learning.
A Systematic Comparison of Robustness in Bayesian Deep Learning on Diabetic Retinopathy Diagnosis Tasks
Work as part of ANL summer 2020 research on uncertainity quanitification methods in graph neural networks
[NeurIPS 2023] Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing
Code accompanying ICLR 2024 paper "Function-space Parameterization of Neural Networks for Sequential Learning"
My excursions in the world of Artificial Neural Networks
Implementing Bayes by Backprop with PyTorch. Applied on time-series prediction.
Benchmarking Bayesian Deep Learning for Out-of-Distribution Detection
Variational continual learning of a conditional diffusion model to generate MNIST. Based on 'Conditional Diffusion MNIST'.
An implementation of natural parameter networks and its extension to GRUs in PyTorch
Active Learning with approximations of Bayesian Convolutional Neural Networks.
Inference Algorithms for Bayesian Deep Learning
Research-repository: Bayesian neural networks for predicting disruptions using EFIT and diagnostic data in KSTAR
Empirical analysis of recent stochastic gradient methods for approximate inference in Bayesian deep learning, including SWA-Gaussian, MultiSWAG, and deep ensembles. See report_localglobal.pdf.
PyTorch implementation of the paper 'Weight Uncertainty in Neural Networks'
From Registration Uncertainty to Segmentation Uncertainty (ISBI 2024)
Codebase for BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts.
Awesome-spatial-temporal-scientific-machine-learning-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about package information. Data Sources Links and Epidemic Repos are also included.
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