ML Collective

Projects

We're proud of the projects ML Collective members have worked on! Each project below is by at least one author with an MLC affiliation or acknowledges MLC research support.

If you're an MLC researcher and would like your project posted here, here's how to add it.

Estimating Example Difficulty Using Variance of Gradients

Chirag Agarwal, Daniel D'souza, Sara Hooker

Published at CVPR 2022

arXiv (pdf) | blog | code

NeuralArTS: Structuring Neural Architecture Search with Type Theory (Student Abstract)

Robert Wu, Nayan Saxena , Rohan Jain

Published at AAAI 2022

arXiv (pdf) | code

Towards One Shot Search Space Poisoning in Neural Architecture Search (Student Abstract)

Nayan Saxena, Robert Wu , Rohan Jain

Published at AAAI 2022

arXiv (pdf) | code

Sign-to-Speech Model for Sign Language Understanding: A Case Study of Nigerian Sign Language

Steven Kolawole, Opeyemi Osakuade, Nayan Saxena, Babatunde K. Olorisade

Published at ML4D Workshop, NeurIPS 2021

arXiv (pdf) | video

Language Models are Few-shot Multilingual Learners

Genta Indra Winata, Andrea Madotto, Zhaojiang Lin, Rosanne Liu, Jason Yosinski, Pascale Fung

Published at MRL Workshop, EMNLP 2021

arXiv (pdf) | code | video

Deep Synoptic Monte Carlo Planning in Reconnaissance Blind Chess

Gregory Clark

Published at NeurIPS 2021

arXiv (pdf)

A Tale Of Two Long Tails

Daniel D'souza, Zach Nussbaum, Chirag Agarwal, Sara Hooker

Published at UDL Workshop, ICML 2021

arXiv (pdf) | code

When does loss-based prioritization fail?

Niel Teng Hu, Xinyu Hu, Rosanne Liu, Sara Hooker, Jason Yosinski

Published at SubSetML Workshop, ICML 2021

arXiv (pdf)

Multi-layer Hebbian networks with modern deep learning frameworks

Thomas Miconi

arXiv (pdf) | code

Scaling Down Deep Learning

Sam Greydanus

arXiv (pdf) | blog | code

Supermasks in Superposition

Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, Ali Farhadi

Published at NeurIPS 2020

arXiv (pdf) | blog | code

Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients

Ashley D. Edwards, Himanshu Sahni, Rosanne Liu, Jane Hung, Ankit Jain, Rui Wang, Adrien Ecoffet, Thomas Miconi, Charles Isbell, Jason Yosinski

Published at ICML 2020

arXiv (pdf) | code | video

Plug and Play Language Models: a Simple Approach to Controlled Text Generation

Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, Rosanne Liu

Published at ICLR 2020

arXiv (pdf) | blog | code | video

LCA: Loss Change Allocation for Neural Network Training

Janice Lan, Rosanne Liu, Hattie Zhou, Jason Yosinski

Published at NeurIPS 2019

arXiv (pdf) | blog | code | video

Hamiltonian Neural Networks

Sam Greydanus, Misko Dzamba, and Jason Yosinski

Published at NeurIPS 2019

arXiv (pdf) | blog | code

Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask

Hattie Zhou, Janice Lan, Rosanne Liu, Jason Yosinski

Published at NeurIPS 2019

arXiv (pdf) | blog | code

Metropolis-Hastings Generative Adversarial Networks

Ryan Turner, Jane Hung, Eric Frank, Yunus Saatci, and Jason Yosinski

Published at ICML 2019

arXiv (pdf) | blog | code

Faster Neural Networks Straight from JPEG

Lionel Gueguen, Alex Sergeev, Ben Kadlec, Rosanne Liu, Jason Yosinski

Published at NeurIPS 2018

arXiv (pdf) | blog | code

An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

Rosanne Liu, Joel Lehman, Piero Molino, Felipe Petroski Such, Eric Frank, Alex Sergeev, Jason Yosinski

Published at NeurIPS 2018

arXiv (pdf) | blog | code | video

Measuring the intrinsic dimension of objective landscapes

Chunyuan Li, Heerad Farkhoor, Rosanne Liu, Jason Yosinski

Published at ICLR 2018

arXiv (pdf) | blog | code | video