Pinned Repositories
Applied-Deep-Learning
Applied Deep Learning
Applied-Deep-Learning-with-Keras
Deep Learning examples with Keras.
DeepHPMs
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
Distributions.jl
A Julia package for probability distributions and associated functions.
emiliocortes.github.io
Build a Jekyll blog in minutes, without touching the command line.
From-0-to-Research-Scientist-resources-guide
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
machine-learning-cheat-sheet
Classical equations and diagrams in machine learning
MachineLearning
Course on Machine Learning and Statistical data Analysis with book at https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/index.html. Contains Linear and Logistic Regression, Neural Networks and Deep Learning methods, Decision Trees, Random forests, Boosting methods and other ensemble methods, support vector machines and central unsupervised learning algorithms.
phygnn
physics-guided neural networks (phygnn)
Physics-Based-Deep-Learning
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
renormalon's Repositories
renormalon/Applied-Deep-Learning
Applied Deep Learning
renormalon/Applied-Deep-Learning-with-Keras
Deep Learning examples with Keras.
renormalon/DeepHPMs
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
renormalon/Distributions.jl
A Julia package for probability distributions and associated functions.
renormalon/emiliocortes.github.io
Build a Jekyll blog in minutes, without touching the command line.
renormalon/From-0-to-Research-Scientist-resources-guide
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
renormalon/machine-learning-cheat-sheet
Classical equations and diagrams in machine learning
renormalon/MachineLearning
Course on Machine Learning and Statistical data Analysis with book at https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/index.html. Contains Linear and Logistic Regression, Neural Networks and Deep Learning methods, Decision Trees, Random forests, Boosting methods and other ensemble methods, support vector machines and central unsupervised learning algorithms.
renormalon/phygnn
physics-guided neural networks (phygnn)
renormalon/Physics-Based-Deep-Learning
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
renormalon/qiskit-machine-learning
Quantum Machine Learning
renormalon/renorm.github.io
The academic web-page
renormalon/ToTTo
ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description. We hope it can serve as a useful research benchmark for high-precision conditional text generation.