rpatrik96/lod-wmm-2019

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rpatrik96/lod-wmm-2019

rpatrik96

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Supplementary code for the paper "Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks" - an accepted paper of LOD2019

pytorch-a2c

A well-documented A2C written in PyTorch

AttA2C

Attention-based Curiosity-driven Exploration in Deep Reinforcement Learning

Jupyter Notebook

3d-tracking

Object tracking with OpenCV based on stereo camera images

ima-vae

This is the code for the paper Embrace the Gap: VAEs perform Independent Mechanism Analysis, showing that optimizing the ELBO is equivalent to optimizing the IMA-regularized log-likelihood under certain assumptions (e.g., small decoder variance).

Jupyter Notebook

nl-causal-representations

This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (particularly, with Nonlinear ICA) can be used to extract the causal graph from an underlying structural equation model (SEM).

pytorch-lightning-wavenet

An implementation of WaveNet using PyTorch & PyTorch Lightning

memristor-fem

Basic EM-field simulation of a memristor with FEM

vae-sam

lti-ica

Independent Component Analysis in Linear Time-Invariant Systems

llm-non-identifiability

Investigating the non-identifiability of Transformers

embedded-software

Software projects for embedded systems