Kento Nozawa's repositories
optuna-wandb
Example codes in the medium post titled "Optuna meets Weights and Biases."
pb-contrastive
#UAI2020 Codes for PAC-Bayesian Contrastive Unsupervised Representation Learning
gap-contrastive-and-supervised-losses
#ICML2022 Experimental codes of "On the Surrogate Gap between Contrastive and Supervised Losses"
Understanding-Negative-Samples
#NeurIPS2021 Codes for Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning
optuna-examples
Examples for https://github.com/optuna/optuna
aim
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
pytorch-OpCounter
Count the MACs / FLOPs of your PyTorch model.
pytorch-pfn-extras
Supplementary components to accelerate research and development in PyTorch
quickshift
A clustering algorithm that first finds the high-density regions (cluster-cores) of the data and then clusters the remaining points by hill-climbing. Such seedings act as more stable and expressive cluster-cores than the singleton modes found by popular algorithm such as mean shift. (https://arxiv.org/abs/1805.07909)
refill
Diverse Parallel Data Synthesis for Cross-Database Adaptation of Text-to-SQL Parsers (EMNLP 2022)
scikit-learn
scikit-learn: machine learning in Python
v11
Workshop on Applications of Pattern Analysis (WAPA) 2010 Proceedings
v16
Active Learning and Experimental Design Workshop
v162
Proceedings of ICML 2022
v202
Proceedings of ICML 2023