Ari S. Morcos

According to our database1, Ari S. Morcos authored at least 52 papers between 2018 and 2024.

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Bibliography

2024
Effective pruning of web-scale datasets based on complexity of concept clusters.
CoRR, 2024

2023
Emergence of Maps in the Memories of Blind Navigation Agents.
AI Matters, June, 2023

lo-fi: distributed fine-tuning without communication.
Trans. Mach. Learn. Res., 2023

Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data.
CoRR, 2023

SIEVE: Multimodal Dataset Pruning Using Image Captioning Models.
CoRR, 2023

On the special role of class-selective neurons in early training.
CoRR, 2023

Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations.
CoRR, 2023

A Cookbook of Self-Supervised Learning.
CoRR, 2023

SemDeDup: Data-efficient learning at web-scale through semantic deduplication.
CoRR, 2023

Stable and low-precision training for large-scale vision-language models.
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.
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.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
The Robustness Limits of SoTA Vision Models to Natural Variation.
CoRR, 2022

Robust Self-Supervised Learning with Lie Groups.
CoRR, 2022

Beyond neural scaling laws: beating power law scaling via data pruning.
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.
Proceedings of the International Conference on Machine Learning, 2022

Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.
Proceedings of the International Conference on Machine Learning, 2022

2021
Trade-offs of Local SGD at Scale: An Empirical Study.
CoRR, 2021

Transformed CNNs: recasting pre-trained convolutional layers with self-attention.
CoRR, 2021

Leveraging background augmentations to encourage semantic focus in self-supervised contrastive learning.
CoRR, 2021

Representation Learning Through Latent Canonicalizations.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks.
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.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

CURI: A Benchmark for Productive Concept Learning Under Uncertainty.
Proceedings of the 38th International Conference on Machine Learning, 2021

Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs.
Proceedings of the 9th International Conference on Learning Representations, 2021

Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs.
Proceedings of the 9th International Conference on Learning Representations, 2021

Width Transfer: On the (In)variance of Width Optimization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Reservoir Transformers.
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.
CoRR, 2020

Towards falsifiable interpretability research.
CoRR, 2020

Linking average- and worst-case perturbation robustness via class selectivity and dimensionality.
CoRR, 2020

Are all negatives created equal in contrastive instance discrimination?
CoRR, 2020

PareCO: Pareto-aware Channel Optimization for Slimmable Neural Networks.
CoRR, 2020

On the relationship between class selectivity, dimensionality, and robustness.
CoRR, 2020

Analyzing Visual Representations in Embodied Navigation Tasks.
CoRR, 2020

Pruning Convolutional Neural Networks with Self-Supervision.
CoRR, 2020

The Generalization-Stability Tradeoff In Neural Network Pruning.
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.
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.
Proceedings of the 8th International Conference on Learning Representations, 2020

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames.
Proceedings of the 8th International Conference on Learning Representations, 2020

The Early Phase of Neural Network Training.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Decentralized Distributed PPO: Solving PointGoal Navigation.
CoRR, 2019

Luck Matters: Understanding Training Dynamics of Deep ReLU Networks.
CoRR, 2019

One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers.
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.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Analyzing biological and artificial neural networks: challenges with opportunities for synergy?
CoRR, 2018

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning.
CoRR, 2018

Learned Deformation Stability in Convolutional Neural Networks.
CoRR, 2018

Insights on representational similarity in neural networks with canonical correlation.
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.
Proceedings of the 35th International Conference on Machine Learning, 2018

On the importance of single directions for generalization.
Proceedings of the 6th International Conference on Learning Representations, 2018


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