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Spotlights
Pratyush Maini · JIVAT NEET KAUR · Anil Palepu · Polina Kirichenko · Revant Teotia
Fri Jul 22 08:40 AM -- 09:30 AM (PDT) @
Author Information
Pratyush Maini (Carnegie Mellon University)
JIVAT NEET KAUR (Microsoft Research, India)
Anil Palepu (Harvard-MIT Health Sciences & Technology)
3rd year PhD student in Department of Health Sciences & Technology, Harvard-MIT. Member of Beam Lab in the Harvard T.H. Chan School of Public Health.
Polina Kirichenko (New York University)
Revant Teotia (Columbia University)
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2021 : Task-agnostic Continual Learning with Hybrid Probabilistic Models »
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2022 : Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization »
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2022 : Finding Spuriously Correlated Visual Attributes »
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2022 : Doubly Right Object Recognition »
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2022 : Characterizing Datapoints via Second-Split Forgetting »
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2022 : Self-Supervision on Images and Text Reduces Reliance on Visual Shortcut Features »
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2022 : Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations »
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2022 : On Feature Learning in the Presence of Spurious Correlations »
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2023 : Towards Modular Machine Learning Pipelines »
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2023 : Model-tuning Via Prompts Makes NLP Models Adversarially Robust »
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2023 : Understanding the Detrimental Class-level Effects of Data Augmentation »
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2023 : TMARS: Improving Visual Representations by Circumventing Text Feature Learning »
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2023 : Conformal Prediction with Large Language Models for Multi-Choice Question Answering »
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2023 : Leveraging Large Scale Models for Identifying and Fixing Deep Neural Networks Biases »
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2023 Poster: Can Neural Network Memorization Be Localized? »
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2021 : Invited Talk 5: Applications of normalizing flows: semi-supervised learning, anomaly detection, and continual learning »
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2020 Poster: Semi-Supervised Learning with Normalizing Flows »
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2020 Poster: Adversarial Robustness Against the Union of Multiple Perturbation Models »
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2019 : poster session I »
Nicholas Rhinehart · Yunhao Tang · Vinay Prabhu · Dian Ang Yap · Alexander Wang · Marc Finzi · Manoj Kumar · You Lu · Abhishek Kumar · Qi Lei · Michael Przystupa · Nicola De Cao · Polina Kirichenko · Pavel Izmailov · Andrew Wilson · Jakob Kruse · Diego Mesquita · Mario Lezcano Casado · Thomas Müller · Keir Simmons · Andrei Atanov -
2019 : Subspace Inference for Bayesian Deep Learning »
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2019 Poster: SWALP : Stochastic Weight Averaging in Low Precision Training »
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2019 Oral: SWALP : Stochastic Weight Averaging in Low Precision Training »
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