• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 149 matches

• 2024
• 
  Wouter A. C. van Amsterdam, Pim A. de Jong, Joost J. C. Verhoeff, Tim Leiner, Rajesh Ranganath:
  From algorithms to action: improving patient care requires causality. BMC Medical Informatics Decis. Mak. 24(3): 111 (2024)
• 
  Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran:
  Robust anomaly detection for particle physics using multi-background representation learning. Mach. Learn. Sci. Technol. 5(3): 35082 (2024)
• 
  Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi M. Schambra, Carlos Fernandez-Granda:
  Quantifying impairment and disease severity using AI models trained on healthy subjects. npj Digit. Medicine 7(1) (2024)
• 
  Aahlad Manas Puli, Nitish Joshi, Yoav Wald, He He, Rajesh Ranganath:
  Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation. Trans. Mach. Learn. Res. 2024 (2024)
• 
  Lily H. Zhang, Rajesh Ranganath, Arya Tafvizi:
  Towards Minimal Targeted Updates of Language Models with Targeted Negative Training. Trans. Mach. Learn. Res. 2024 (2024)
• 
  Meera Gopinath Sujatha, Rajesh Godasu, Prakash Ranganathan:
  Classification of Microcystins Based on Temperature Data in North Dakota Lake. AIIoT 2024: 142-150
• 
  Michael S. Albergo, Mark Goldstein, Nicholas Matthew Boffi, Rajesh Ranganath, Eric Vanden-Eijnden:
  Stochastic Interpolants with Data-Dependent Couplings. ICML 2024
• 
  Raghav Singhal, Mark Goldstein, Rajesh Ranganath:
  What's the score? Automated Denoising Score Matching for Nonlinear Diffusions. ICML 2024
• 
  Chen-Yu Yen, Raghav Singhal, Umang Sharma, Rajesh Ranganath, Sumit Chopra, Lerrel Pinto:
  Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction. ICML 2024
• 
  Yifan Yuan, Ren Wang, Narayan Ranganathan, Nikhil Rao, Sanjay Kumar, Philip Lantz, Vivekananthan Sanjeepan, Jorge Cabrera, Atul Kwatra, Rajesh Sankaran, Ipoom Jeong, Nam Sung Kim:
  Intel Accelerators Ecosystem: An SoC-Oriented Perspective : Industry Product. ISCA 2024: 848-862
• 
  Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran:
  Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning. CoRR abs/2401.08777 (2024)
• 
  Laura Manduchi, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin:
  On the Challenges and Opportunities in Generative AI. CoRR abs/2403.00025 (2024)
• 
  Angelica Chen, Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho:
  Preference Learning Algorithms Do Not Learn Preference Rankings. CoRR abs/2405.19534 (2024)
• 
  Chen-Yu Yen, Raghav Singhal, Umang Sharma, Rajesh Ranganath, Sumit Chopra, Lerrel Pinto:
  Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction. CoRR abs/2406.04318 (2024)
• 
  Lily H. Zhang, Rajesh Ranganath, Arya Tafvizi:
  Towards Minimal Targeted Updates of Language Models with Targeted Negative Training. CoRR abs/2406.13660 (2024)
• 
  Raghav Singhal, Mark Goldstein, Rajesh Ranganath:
  What's the score? Automated Denoising Score Matching for Nonlinear Diffusions. CoRR abs/2407.07998 (2024)
• 2023
• 
  Nihal Murali, Aahlad Manas Puli, Ke Yu, Rajesh Ranganath, Kayhan Batmanghelich:
  Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics. Trans. Mach. Learn. Res. 2023 (2023)
• 
  Lily H. Zhang, Rajesh Ranganath:
  Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection. AAAI 2023: 15305-15312
• 
  Neil Jethani, Adriel Saporta, Rajesh Ranganath:
  Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation. AISTATS 2023: 8925-8953
• 
  Mukund Sudarshan, Aahlad Manas Puli, Wesley Tansey, Rajesh Ranganath:
  DIET: Conditional independence testing with marginal dependence measures of residual information. AISTATS 2023: 10343-10367
• 
  Raghav Singhal, Mark Goldstein, Rajesh Ranganath:
  Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions. ICLR 2023
• 
  Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner:
  An Effective Meaningful Way to Evaluate Survival Models. ICML 2023: 28244-28276
• 
  Rhys Compton, Lily H. Zhang, Aahlad Manas Puli, Rajesh Ranganath:
  When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations. MLHC 2023: 110-127
• 
  Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath:
  Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy. NeurIPS 2023
• 
  Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary C. Lipton, Rajesh Ranganath, Iñigo Urteaga, Serene Yeung:
  Machine Learning for Healthcare Conference, MLHC 2023, 11-12 August 2023, New York, USA. Proceedings of Machine Learning Research 219, PMLR 2023 [contents]
• 
  Raghav Singhal, Mukund Sudarshan, Anish Mahishi, Sri Kaushik, Luke Ginocchio, Angela Tong, Hersh Chandarana, Daniel K. Sodickson, Rajesh Ranganath, Sumit Chopra:
  On the Feasibility of Machine Learning Augmented Magnetic Resonance for Point-of-Care Identification of Disease. CoRR abs/2301.11962 (2023)
• 
  Lily H. Zhang, Rajesh Ranganath:
  Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection. CoRR abs/2302.04132 (2023)
• 
  Raghav Singhal, Mark Goldstein, Rajesh Ranganath:
  Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions. CoRR abs/2302.07261 (2023)
• 
  Nihal Murali, Aahlad Manas Puli, Ke Yu, Rajesh Ranganath, Kayhan Batmanghelich:
  Shortcut Learning Through the Lens of Early Training Dynamics. CoRR abs/2302.09344 (2023)
• 
  Neil Jethani, Adriel Saporta, Rajesh Ranganath:
  Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation. CoRR abs/2302.12893 (2023)

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