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2020 – today
- 2024
[c11]Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer:
Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples. AAAI 2024: 12331-12339- [c10]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang:
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. ICLR 2024 - 2023
- [c9]Jay Nandy
, Jatin Chauhan, Rishi Saket, Aravindan Raghuveer:
Non-Uniform Adversarial Perturbations for Discrete Tabular Datasets. CIKM 2023: 1887-1896 - [c8]Jatin Chauhan, Xiaoxuan Wang, Wei Wang:
Learning under Label Proportions for Text Classification. EMNLP (Findings) 2023: 12210-12223 - [c7]Yihan Wang, Jatin Chauhan, Wei Wang, Cho-Jui Hsieh:
Universality and Limitations of Prompt Tuning. NeurIPS 2023 - [i11]Yihan Wang, Jatin Chauhan, Wei Wang, Cho-Jui Hsieh:
Universality and Limitations of Prompt Tuning. CoRR abs/2305.18787 (2023) - [i10]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang:
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. CoRR abs/2310.00115 (2023) - [i9]Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer:
Improving Fairness-Accuracy tradeoff with few Test Samples under Covariate Shift. CoRR abs/2310.07535 (2023) - [i8]Jatin Chauhan, Xiaoxuan Wang, Wei Wang:
Learning under Label Proportions for Text Classification. CoRR abs/2310.11707 (2023) - 2022
- [c6]Jay Nandy, Rishi Saket, Prateek Jain, Jatin Chauhan, Balaraman Ravindran, Aravindan Raghuveer:
Domain-Agnostic Contrastive Representations for Learning from Label Proportions. CIKM 2022: 1542-1551 - [c5]Jatin Chauhan, Manohar Kaul:
BERTops: Studying BERT Representations under a Topological Lens. IJCNN 2022: 1-8 - [c4]Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran:
Multi-Variate Time Series Forecasting on Variable Subsets. KDD 2022: 76-86 - [i7]Jatin Chauhan, Manohar Kaul:
BERTops: Studying BERT Representations under a Topological Lens. CoRR abs/2205.00953 (2022) - [i6]Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran:
Multi-Variate Time Series Forecasting on Variable Subsets. CoRR abs/2206.12626 (2022) - 2021
- [i5]Jatin Chauhan, Karan Bhukar, Manohar Kaul:
Target Model Agnostic Adversarial Attacks with Query Budgets on Language Understanding Models. CoRR abs/2106.07047 (2021) - [i4]Jatin Chauhan, Priyanshu Gupta, Pasquale Minervini:
A Probabilistic Framework for Knowledge Graph Data Augmentation. CoRR abs/2110.13205 (2021) - 2020
- [c3]Jatin Chauhan, Deepak Nathani, Manohar Kaul:
Few-Shot Learning on graphs via super-Classes based on Graph spectral Measures. ICLR 2020 - [c2]Charu Sharma, Jatin Chauhan, Manohar Kaul:
Learning Representations using Spectral-Biased Random Walks on Graphs. IJCNN 2020: 1-8 - [i3]Jatin Chauhan, Deepak Nathani, Manohar Kaul:
Few-Shot Learning on Graphs via Super-Classes based on Graph Spectral Measures. CoRR abs/2002.12815 (2020) - [i2]Charu Sharma, Jatin Chauhan, Manohar Kaul:
Learning Representations using Spectral-Biased Random Walks on Graphs. CoRR abs/2005.09752 (2020)
2010 – 2019
- 2019
- [c1]Deepak Nathani, Jatin Chauhan, Charu Sharma, Manohar Kaul:
Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs. ACL (1) 2019: 4710-4723 - [i1]Deepak Nathani, Jatin Chauhan, Charu Sharma, Manohar Kaul:
Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs. CoRR abs/1906.01195 (2019)
Coauthor Index
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last updated on 2024-08-08 20:14 CEST by the dblp team
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