wiegerw

Pinned Repositories

mCRL2
The Git repository for the mCRL2 toolset.
Language:C++87 11 1.7k36
aitools
C++ library that contains basic AI data structures and algorithm, in particular decision trees and probabilistic circuits.
Language:C++00
blocks
Python script for solving 2D and 3D block puzzles
Language:Python00
cm-draughtsboard
A JavaScript draughtsboard component that is rendered in SVG.
Language:JavaScript21
CONEstrip
An implementation of the CONEstrip algorithms using python and z3
Language:Python10
draughts
A C++ library for international draughts, based on the program Scan. This library has been used in several master thesis projects.
Language:C++22
gambatools
A library for formal language education. It contains support for DFAs, NFAs, PDAs, Turing machines, context free grammars and regular expressions.
Language:Python20
mackerel
Language:C++10
nerva
C++ library for neural networks with python bindings.
Language:C++10
pdn
The official portable draughts notation standard PDN 3.0
Language:Python20

wiegerw's Repositories

wiegerw/cm-draughtsboard
A JavaScript draughtsboard component that is rendered in SVG.
Language:JavaScript21
wiegerw/draughts
A C++ library for international draughts, based on the program Scan. This library has been used in several master thesis projects.
Language:C++22
wiegerw/gambatools
A library for formal language education. It contains support for DFAs, NFAs, PDAs, Turing machines, context free grammars and regular expressions.
Language:Python20
wiegerw/pdn
The official portable draughts notation standard PDN 3.0
Language:Python20
wiegerw/CONEstrip
An implementation of the CONEstrip algorithms using python and z3
Language:Python10
wiegerw/mackerel
Language:C++10
wiegerw/nerva
C++ library for neural networks with python bindings.
Language:C++10
wiegerw/aitools
C++ library that contains basic AI data structures and algorithm, in particular decision trees and probabilistic circuits.
Language:C++00
wiegerw/blocks
Python script for solving 2D and 3D block puzzles
Language:Python00
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).
Language:CMake00
wiegerw/dparser
A Scannerless GLR parser/parser generater.
wiegerw/draughtsboard
Javascript draughts board
wiegerw/egdb_intl
Functions to access the kingsrow international draughts endgame database
wiegerw/GeFs
Generative Forests in Python
Language: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
Language:Python
wiegerw/Lyra
A simple to use, composable, command line parser for C++ 11 and beyond
wiegerw/minimal-cnpy
Language:C++
wiegerw/nerva-jax
Implementation of neural networks in JAX
Language:Python
wiegerw/nerva-numpy
Implementation of neural networks in NumPy
Language:Python
wiegerw/nerva-sympy
Implementation of neural networks in SymPy
Language:Python
wiegerw/nerva-tensorflow
Implementation of neural networks in TensorFlow
Language:Python
wiegerw/nerva-torch
Implementation of neural networks in PyTorch
Language:Python
wiegerw/nerva_stub
Stub for the Nerva package
Language:Python
wiegerw/pydraughts
A draughts (checkers) library for Python with move generation, PDN reading and writing, engine communication and balloted openings
wiegerw/pypi_example
Language:Python
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
Language:Python
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
Language:Python
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).
Language:Python
wiegerw/Thesis_Thijs_joosten
The code used in the master thesis of Thijs Joosten, 13-01-2023