Ari S. Morcos

According to our database, Ari S. Morcos authored at least 53 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Brevity is the soul of wit: Pruning long files for code generation.

Aaditya K. Singh, Yu Yang, Kushal Tirumala, Mostafa Elhoushi, Ari S. Morcos

CoRR, 2024

Effective pruning of web-scale datasets based on complexity of concept clusters.

Amro Abbas, Evgenia Rusak, Kushal Tirumala, Wieland Brendel, Kamalika Chaudhuri, Ari S. Morcos

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Sieve: Multimodal Dataset Pruning Using Image Captioning Models.

Anas Mahmoud, Mostafa Elhoushi, Amro Abbas, Yu Yang, Newsha Ardalani, Hugh Leather, Ari S. Morcos

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Emergence of Maps in the Memories of Blind Navigation Agents.

Erik Wijmans, Manolis Savva, Irfan Essa, Stefan Lee, Ari S. Morcos, Dhruv Batra

AI Matters, June, 2023

lo-fi: distributed fine-tuning without communication.

Mitchell Wortsman, Suchin Gururangan, Shen Li, Ali Farhadi, Ludwig Schmidt, Michael G. Rabbat, Ari S. Morcos

Trans. Mach. Learn. Res., 2023

On the special role of class-selective neurons in early training.

Omkar Ranadive, Nikhil Thakurdesai, Ari S. Morcos, Matthew L. Leavitt, Stéphane Deny

Trans. Mach. Learn. Res., 2023

The Robustness Limits of SoTA Vision Models to Natural Variation.

Mark Ibrahim, Quentin Garrido, Ari S. Morcos, Diane Bouchacourt

Trans. Mach. Learn. Res., 2023

Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data.

Yu Yang, Aaditya K. Singh, Mostafa Elhoushi, Anas Mahmoud, Kushal Tirumala, Fabian Gloeckle, Baptiste Rozière, Carole-Jean Wu, Ari S. Morcos, Newsha Ardalani

CoRR, 2023

Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations.

Shashank Shekhar, Florian Bordes, Pascal Vincent, Ari Morcos

CoRR, 2023

A Cookbook of Self-Supervised Learning.

Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum

CoRR, 2023

SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

Amro Abbas, Kushal Tirumala, Daniel Simig, Surya Ganguli, Ari S. Morcos

CoRR, 2023

Stable and low-precision training for large-scale vision-language models.

Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, Ludwig Schmidt

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

D4: Improving LLM Pretraining via Document De-Duplication and Diversification.

Kushal Tirumala, Daniel Simig, Armen Aghajanyan, Ari Morcos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning.

Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Robust Self-Supervised Learning with Lie Groups.

Mark Ibrahim, Diane Bouchacourt, Ari S. Morcos

CoRR, 2022

Beyond neural scaling laws: beating power law scaling via data pruning.

Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari Morcos

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

COAT: Measuring Object Compositionality in Emergent Representations.

Sirui Xie, Ari S. Morcos, Song-Chun Zhu, Ramakrishna Vedantam

Proceedings of the International Conference on Machine Learning, 2022

Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo Lopes, Ari S. Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, Ludwig Schmidt

Proceedings of the International Conference on Machine Learning, 2022

2021

Trade-offs of Local SGD at Scale: An Empirical Study.

Jose Javier Gonzalez Ortiz, Jonathan Frankle, Mike Rabbat, Ari S. Morcos, Nicolas Ballas

CoRR, 2021

Transformed CNNs: recasting pre-trained convolutional layers with self-attention.

Stéphane d'Ascoli, Levent Sagun, Giulio Biroli, Ari Morcos

CoRR, 2021

Leveraging background augmentations to encourage semantic focus in self-supervised contrastive learning.

Chaitanya K. Ryali, David J. Schwab, Ari S. Morcos

CoRR, 2021

Representation Learning Through Latent Canonicalizations.

Or Litany, Ari Morcos, Srinath Sridhar, Leonidas J. Guibas, Judy Hoffman

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks.

Ting-Wu Chin, Ari S. Morcos, Diana Marculescu

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Grounding inductive biases in natural images: invariance stems from variations in data.

Diane Bouchacourt, Mark Ibrahim, Ari S. Morcos

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases.

Stéphane d'Ascoli, Hugo Touvron, Matthew L. Leavitt, Ari S. Morcos, Giulio Biroli, Levent Sagun

Proceedings of the 38th International Conference on Machine Learning, 2021

CURI: A Benchmark for Productive Concept Learning Under Uncertainty.

Ramakrishna Vedantam, Arthur Szlam, Maximilian Nickel, Ari Morcos, Brenden M. Lake

Proceedings of the 38th International Conference on Machine Learning, 2021

Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs.

Matthew L. Leavitt, Ari S. Morcos

Proceedings of the 9th International Conference on Learning Representations, 2021

Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs.

Jonathan Frankle, David J. Schwab, Ari S. Morcos

Proceedings of the 9th International Conference on Learning Representations, 2021

Width Transfer: On the (In)variance of Width Optimization.

Ting-Wu Chin, Diana Marculescu, Ari S. Morcos

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Reservoir Transformers.

Sheng Shen, Alexei Baevski, Ari S. Morcos, Kurt Keutzer, Michael Auli, Douwe Kiela

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Reservoir Transformer.

Sheng Shen, Alexei Baevski, Ari S. Morcos, Kurt Keutzer, Michael Auli, Douwe Kiela

CoRR, 2020

Towards falsifiable interpretability research.

Matthew L. Leavitt, Ari S. Morcos

CoRR, 2020

Linking average- and worst-case perturbation robustness via class selectivity and dimensionality.

Matthew L. Leavitt, Ari S. Morcos

CoRR, 2020

Are all negatives created equal in contrastive instance discrimination?

Tiffany Tianhui Cai, Jonathan Frankle, David J. Schwab, Ari S. Morcos

CoRR, 2020

PareCO: Pareto-aware Channel Optimization for Slimmable Neural Networks.

Ting-Wu Chin, Ari S. Morcos, Diana Marculescu

CoRR, 2020

On the relationship between class selectivity, dimensionality, and robustness.

Matthew L. Leavitt, Ari S. Morcos

CoRR, 2020

Analyzing Visual Representations in Embodied Navigation Tasks.

Erik Wijmans, Julian Straub, Dhruv Batra, Irfan Essa, Judy Hoffman, Ari Morcos

CoRR, 2020

Pruning Convolutional Neural Networks with Self-Supervision.

Mathilde Caron, Ari Morcos, Piotr Bojanowski, Julien Mairal, Armand Joulin

CoRR, 2020

The Generalization-Stability Tradeoff In Neural Network Pruning.

Brian R. Bartoldson, Ari S. Morcos, Adrian Barbu, Gordon Erlebacher

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Plan2Vec: Unsupervised Representation Learning by Latent Plans.

Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP.

Haonan Yu, Sergey Edunov, Yuandong Tian, Ari S. Morcos

Proceedings of the 8th International Conference on Learning Representations, 2020

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames.

Erik Wijmans, Abhishek Kadian, Ari Morcos, Stefan Lee, Irfan Essa, Devi Parikh, Manolis Savva, Dhruv Batra

Proceedings of the 8th International Conference on Learning Representations, 2020

The Early Phase of Neural Network Training.

Jonathan Frankle, David J. Schwab, Ari S. Morcos

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Decentralized Distributed PPO: Solving PointGoal Navigation.

Erik Wijmans, Abhishek Kadian, Ari Morcos, Stefan Lee, Irfan Essa, Devi Parikh, Manolis Savva, Dhruv Batra

CoRR, 2019

Luck Matters: Understanding Training Dynamics of Deep ReLU Networks.

Yuandong Tian, Tina Jiang, Qucheng Gong, Ari S. Morcos

CoRR, 2019

One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers.

Ari S. Morcos, Haonan Yu, Michela Paganini, Yuandong Tian

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning to Make Analogies by Contrasting Abstract Relational Structure.

Felix Hill, Adam Santoro, David G. T. Barrett, Ari S. Morcos, Timothy P. Lillicrap

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Analyzing biological and artificial neural networks: challenges with opportunities for synergy?

David G. T. Barrett, Ari S. Morcos, Jakob H. Macke

CoRR, 2018

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning.

Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio García Castañeda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, Nicolas Sonnerat, Tim Green, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, Thore Graepel

CoRR, 2018

Learned Deformation Stability in Convolutional Neural Networks.

Avraham Ruderman, Neil C. Rabinowitz, Ari S. Morcos, Daniel Zoran

CoRR, 2018

Insights on representational similarity in neural networks with canonical correlation.

Ari S. Morcos, Maithra Raghu, Samy Bengio

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Measuring abstract reasoning in neural networks.

Adam Santoro, Felix Hill, David G. T. Barrett, Ari S. Morcos, Timothy P. Lillicrap

Proceedings of the 35th International Conference on Machine Learning, 2018

On the importance of single directions for generalization.

Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew M. Botvinick

Proceedings of the 6th International Conference on Learning Representations, 2018