Pinned Repositories
Compute-Canada-Guidelines
Guidelines on basic usage of Compute Canada's supercomputer resources
deepparse
Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning
deepparse-address-data
Multinational Structured Address Data
domain_adaptation_of_linear_classifiers
Learning algorithm described in "A New PAC-Bayesian Perspective on Domain Adaptation" (see http://arxiv.org/abs/1506.04573)
domain_adversarial_neural_network
Domain Adaptation Representation Learning Algorithm (as published in JMLR 2016)
graal-poster
Latex poster package of the GRAAL group
majority-vote-bounds
PAC-Bayesian bounds computation related to "Risk Bounds for the Majority Vote [...]" (JMLR 2015)
OfflineRLReadingGroup
Offline Reinforcement Learning Reading Group
PAC-Bayes_sample_compress_for_kernel_methods
Learning algorithms introduced in "A PAC-Bayes Sample Compression Approach to Kernel Methods" (ICML 2011)
poutyne
A simplified framework and utilities for PyTorch
GRAAL/GRAIL's Repositories
GRAAL-Research/poutyne
A simplified framework and utilities for PyTorch
GRAAL-Research/deepparse
Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning
GRAAL-Research/domain_adversarial_neural_network
Domain Adaptation Representation Learning Algorithm (as published in JMLR 2016)
GRAAL-Research/deepparse-address-data
Multinational Structured Address Data
GRAAL-Research/OfflineRLReadingGroup
Offline Reinforcement Learning Reading Group
GRAAL-Research/Compute-Canada-Guidelines
Guidelines on basic usage of Compute Canada's supercomputer resources
GRAAL-Research/domain_adaptation_of_linear_classifiers
Learning algorithm described in "A New PAC-Bayesian Perspective on Domain Adaptation" (see http://arxiv.org/abs/1506.04573)
GRAAL-Research/PAC-Bayes_sample_compress_for_kernel_methods
Learning algorithms introduced in "A PAC-Bayes Sample Compression Approach to Kernel Methods" (ICML 2011)
GRAAL-Research/graal-poster
Latex poster package of the GRAAL group
GRAAL-Research/majority-vote-bounds
PAC-Bayesian bounds computation related to "Risk Bounds for the Majority Vote [...]" (JMLR 2015)
GRAAL-Research/risc
RISC, an open-source Python package data generator. RISC generates look-alike automobile insurance contracts based on the Quebec regulatory insurance form in French and English.
GRAAL-Research/pytorch-gpu-testing
Small script to test that PyTorch works with the current GPU(s).
GRAAL-Research/Transductive-PAC-Bayes
PAC-Bayesian bounds computation related to "PAC-Bayesian Theory for Transductive Learning" (AISTATS 2014)
GRAAL-Research/graal-website
GRAAL-Research/IP-publishing
Instruction and code to publish your server IP address on reboot.
GRAAL-Research/MinCq
GRAAL-Research/training-framework
A training framework built with Hydra 🐲, Lightning ⚡ and MLflow 🌊
GRAAL-Research/csmd
"Continuous Scale Meaning Dataset" used for "MeaningBERT: Assessing Meaning Preservation Between Sentences"
GRAAL-Research/FCCLC
French Canadian complexity level corpus
GRAAL-Research/graal-containers
Several Dockerfiles supporting our research
GRAAL-Research/graal-utils
Utilitary tools
GRAAL-Research/gs-kernel
The generic string kernel for amino acid sequence comparison
GRAAL-Research/Neural-Network
Neural Netwok compatible version with scikit learn
GRAAL-Research/tcc
Text Complexity Computer (TCC) is a package to compute various complexity metrics on text
GRAAL-Research/icscm
Invariant Causal Set Covering Machine
GRAAL-Research/MeaningBERT
MeaningBERT: Assessing Meaning Preservation Between Sentences
GRAAL-Research/cgi-sysadmin
GRAAL-Research/graal-tikz
Standalone TikZ picture of machine learning figure
GRAAL-Research/poutyne-external-assets
GRAAL-Research/shallow-planning-partial-observability
Code accompanying the article from neurips:...