Comparison of the impact the Fast Gradient Sign Attack has on a Deep Neural Networks and a Bayesian Neural Networks.
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Updated
Mar 24, 2020 - Python
Comparison of the impact the Fast Gradient Sign Attack has on a Deep Neural Networks and a Bayesian Neural Networks.
Probabilistic artificial intelligence exercises
Deep Bayesian Optimization for Problems with High-Dimensional Structure
Active Learning with approximations of Bayesian Convolutional Neural Networks.
Inference Algorithms for Bayesian Deep Learning
my blog
Neural Network based Stochastic Blockmodel using Variational Inference
For an assignment at LSE, I deployed and evaluated a number of Bayesian machine-learning techniques based on their capabilities to correctly distinguish benign from malignant tumours.
Probabilistic approach to neural nets - modern scalable approximate inference methods
Team programming exercises for the course unit "Probabilistic Artificial Intelligence", ETH Zurich
The M.Sc. Thesis of Bent Harnist (2022) at Aalto University, "Probabilistic Precipitation Nowcasting Using Bayesian Convolutional Neural Networks"
Code for the research paper Meta-learning with hierarchical models based on similarity of causal mechanisms
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors paper presented @ICLR2024
Project on using control variates for bayesian neural networks
Full Log-Likelihood Heteroskedastic Regression with Deep Neural Networks and Tensorflow
Bayesian Structured Time Series Analysis with Parallel Tempering for Stock Market Prediction
AIS algorithm for BNN inference
Reimplementation of Sparse Variational Dropout in Keras-Core/Keras 3.0
This repository contains code and resources for my thesis project on uncertainty estimation in computed tomography (CT) scan modeling. Explore Bayesian and deterministic neural network architectures for CT analysis and compare their effectiveness in quantifying uncertainty.
A naive bayesian classifier which tells you if an ICO is a scam based on it's whitepaper abstract
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