Pinned Repositories
mCRL2
The Git repository for the mCRL2 toolset.
aitools
C++ library that contains basic AI data structures and algorithm, in particular decision trees and probabilistic circuits.
cm-draughtsboard
A JavaScript draughtsboard component that is rendered in SVG.
CONEstrip
An implementation of the CONEstrip algorithms using python and z3
draughts
A C++ library for international draughts, based on the program Scan. This library has been used in several master thesis projects.
gambatools
A library for formal language education. It contains support for DFAs, NFAs, PDAs, Turing machines, context free grammars and regular expressions.
mackerel
nerva
C++ and Python libraries for neural networks.
nerva-colwise
A C++ library for neural networks
pdn
The official portable draughts notation standard PDN 3.0
wiegerw's Repositories
wiegerw/nerva
C++ and Python libraries for neural networks.
wiegerw/gambatools
A library for formal language education. It contains support for DFAs, NFAs, PDAs, Turing machines, context free grammars and regular expressions.
wiegerw/cm-draughtsboard
A JavaScript draughtsboard component that is rendered in SVG.
wiegerw/draughts
A C++ library for international draughts, based on the program Scan. This library has been used in several master thesis projects.
wiegerw/pdn
The official portable draughts notation standard PDN 3.0
wiegerw/CONEstrip
An implementation of the CONEstrip algorithms using python and z3
wiegerw/nerva-jax
Implementation of neural networks in JAX
wiegerw/aitools
C++ library that contains basic AI data structures and algorithm, in particular decision trees and probabilistic circuits.
wiegerw/blocks
Python script for solving 2D and 3D block puzzles
wiegerw/data-parallel-CPP
Source code for 'Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL' by James Reinders, Ben Ashbaugh, James Brodman, Michael Kinsner, John Pennycook, Xinmin Tian (Apress, 2020).
wiegerw/asciidoc-demo
wiegerw/draughtsboard
Javascript draughts board
wiegerw/GeFs
Generative Forests in Python
wiegerw/In-Time-Over-Parameterization
[ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
wiegerw/Lyra
A simple to use, composable, command line parser for C++ 11 and beyond
wiegerw/minimal-cnpy
wiegerw/nerva-numpy
Implementation of neural networks in NumPy
wiegerw/nerva-rowwise
A C++ library for neural networks
wiegerw/nerva-sympy
Implementation of neural networks in SymPy
wiegerw/nerva-tensorflow
Implementation of neural networks in TensorFlow
wiegerw/nerva-torch
Implementation of neural networks in PyTorch
wiegerw/nerva_stub
Stub for the Nerva package
wiegerw/pyampute
Missing data amputation and exploration functions for Python
wiegerw/pydraughts
A draughts (checkers) library for Python with move generation, PDN reading and writing, engine communication and balloted openings
wiegerw/pypi_example
wiegerw/Random_Pruning
[ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
wiegerw/rigl
End-to-end training of sparse deep neural networks with little-to-no performance loss.
wiegerw/SET-MLP-ONE-MILLION-NEURONS
[Neural Computing and Applications] "Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware" by Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy
wiegerw/sparse-evolutionary-artificial-neural-networks
Always sparse. Never dense. But never say never. A repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).
wiegerw/Thesis_Thijs_joosten
The code used in the master thesis of Thijs Joosten, 13-01-2023