Reading List

This repository collates the papers I am reading for my MSCS thesis.

2015 and later

Paper	Method	Venue	Code
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss	SNNL	ICML 2019
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models	MMVAE	NeurIPS 2019	PyTorch
Multimodal Generative Models for Scalable Weakly-Supervised Learning	MVAE	NeurIPS 2018	PyTorch
Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization	SS AVTS	NeurIPS 2018
Cooperative neural networks: Exploiting prior independence structure for improved classification	CoNN	NeurIPS 2018	PyTorch
Learning to Specialize with Knowledge Distillation for Visual Question Answering	MCL-KD	NeurIPS 2018	PyTorch
KATE: K-Competitive Autoencoder for Text	KATE	KDD 2017	Keras
Distilling the Knowledge in Neural Networks	KD	NeurIPS 2015 Workshop
A network of deep neural networks for distant speech recognition	CN-DNN	ICASSP 2017
Cooperative Training for Generative Modeling of Discrete Data	CoT	ICML 2019
Learning a Text-Video Embedding from Incomplete and Heterogeneous Data	MEE		PyTorch
MIX'EM: Unsupervised Image Classification using a Mixture of Embeddings	MIX'EM	ACCV 2020
Confident Multiple Choice Learning	CMCL	ICML 2017	TensorFlow
Stochastic Multiple Choice Learning	sMCL	NeurIPS 2016

2014 and older

Paper	Method	Venue	Code
Multiple Choice Learning: Learning to Produce Multiple Structured Outputs	MCL	NeurIPS 2012
A Cooperative Ensemble Learning System	CELS	IJCNN 1998