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Publication search results
found 471 matches
- 2024
- Gianluca Detommaso, Alberto Gasparin, Michele Donini, Matthias W. Seeger, Andrew Gordon Wilson, Cédric Archambeau:
Fortuna: A Library for Uncertainty Quantification in Deep Learning. J. Mach. Learn. Res. 25: 238:1-238:7 (2024) - Sam Simmonds, Leo K. Cheng, Wharengaro Ruha, Andrew J. Taberner, Peng Du, Timothy R. Angeli-Gordon:
Measurement and Analysis of In Vivo Gastroduodenal Slow Wave Patterns Using Anatomically-Specific Cradles and Electrodes. IEEE Trans. Biomed. Eng. 71(4): 1289-1297 (2024) - Tim G. J. Rudner, Ya Shi Zhang, Andrew Gordon Wilson, Julia Kempe:
Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors. AISTATS 2024: 127-135 - Kaan Demir, Bach Hoai Nguyen, Jeremy S. Rooney, Bing Xue, Mengjie Zhang, Kirill Lagutin, Andrew MacKenzie, Keith C. Gordon, Daniel P. Killeen:
Improving Inference of Biochemical Composition in Marine Biomass via Genetic Algorithm-Based Feature Selection on Raman Spectroscopic Data. CEC 2024: 1-8 - Andrew S. Gordon, Andrew Feng:
Combining the Predictions of Out-of-Domain Classifiers Using Etcetera Abduction. CISS 2024: 1-6 - Ankur Chemburkar, Andrew S. Gordon, Andrew Feng:
Evaluating Vision-Language Models on the TriangleCOPA Benchmark. FLAIRS 2024 - Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick, Zachary W. Ulissi:
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text. ICLR 2024 - Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mido Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas:
Modeling Caption Diversity in Contrastive Vision-Language Pretraining. ICML 2024 - Sanae Lotfi, Marc Anton Finzi, Yilun Kuang, Tim G. J. Rudner, Micah Goldblum, Andrew Gordon Wilson:
Non-Vacuous Generalization Bounds for Large Language Models. ICML 2024 - Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang:
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. ICML 2024 - Shikai Qiu, Boran Han, Danielle C. Maddix, Shuai Zhang, Bernie Wang, Andrew Gordon Wilson:
Transferring Knowledge From Large Foundation Models to Small Downstream Models. ICML 2024 - Shikai Qiu, Andres Potapczynski, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson:
Compute Better Spent: Replacing Dense Layers with Structured Matrices. ICML 2024 - Shraddha Barke, Christian Pölitz, Carina Negreanu, Benjamin Zorn, José Cambronero, Andrew D. Gordon, Vu Le, Elnaz Nouri, Nadia Polikarpova, Advait Sarkar, Brian Slininger, Neil Toronto, Jack Williams:
Solving Data-centric Tasks using Large Language Models. NAACL-HLT (Findings) 2024: 626-638 - Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson:
Understanding the Detrimental Class-level Effects of Data Augmentation. CoRR abs/2401.01764 (2024) - Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang:
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR abs/2402.00809 (2024) - Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick, Zachary W. Ulissi:
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text. CoRR abs/2402.04379 (2024) - Shraddha Barke, Christian Pölitz, Carina Suzana Negreanu, Benjamin G. Zorn, José Cambronero, Andrew D. Gordon, Vu Le, Elnaz Nouri, Nadia Polikarpova, Advait Sarkar, Brian Slininger, Neil Toronto, Jack Williams:
Solving Data-centric Tasks using Large Language Models. CoRR abs/2402.11734 (2024) - Simone Riggi, Grazia Umana, C. Trigilio, Cristobal Bordiu, Filomena Bufano, Adriano Ingallinera, F. Cavallaro, Yjan Gordon, Ray P. Norris, G. Gürkan, P. Leto, C. Buemi, S. Loru, Andrew M. Hopkins, Miroslav D. Filipovic, Thomas Cecconello:
Classification of compact radio sources in the Galactic plane with supervised machine learning. CoRR abs/2402.15232 (2024) - Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang:
Chronos: Learning the Language of Time Series. CoRR abs/2403.07815 (2024) - Tim G. J. Rudner, Ya Shi Zhang, Andrew Gordon Wilson, Julia Kempe:
Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors. CoRR abs/2403.09869 (2024) - Nikhel Gupta, Ray P. Norris, Zeeshan Hayder, Minh Huynh, Lars Petersson, X. Rosalind Wang, Andrew M. Hopkins, Heinz Andernach, Yjan Gordon, Simone Riggi, Miranda Yew, Evan J. Crawford, Bärbel S. Koribalski, Miroslav D. Filipovic, Anna D. Kapinska, Stanislav Shabala, Tessa Vernstrom, Joshua R. Marvil:
RG-CAT: Detection Pipeline and Catalogue of Radio Galaxies in the EMU Pilot Survey. CoRR abs/2403.14235 (2024) - Hossein Souri, Arpit Bansal, Hamid Kazemi, Liam Fowl, Aniruddha Saha, Jonas Geiping, Andrew Gordon Wilson, Rama Chellappa, Tom Goldstein, Micah Goldblum:
Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion. CoRR abs/2403.16365 (2024) - Ian Drosos, Advait Sarkar, Andrew D. Gordon:
"My toxic trait is thinking I'll remember this": gaps in the learner experience of video tutorials for feature-rich software. CoRR abs/2404.07114 (2024) - Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mahmoud Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas:
Modeling Caption Diversity in Contrastive Vision-Language Pretraining. CoRR abs/2405.00740 (2024) - Shikai Qiu, Andres Potapczynski, Marc Finzi, Micah Goldblum, Andrew Gordon Wilson:
Compute Better Spent: Replacing Dense Layers with Structured Matrices. CoRR abs/2406.06248 (2024) - Shikai Qiu, Boran Han, Danielle C. Maddix, Shuai Zhang, Yuyang Wang, Andrew Gordon Wilson:
Transferring Knowledge from Large Foundation Models to Small Downstream Models. CoRR abs/2406.07337 (2024) - Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine M. Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson:
Large Language Models Must Be Taught to Know What They Don't Know. CoRR abs/2406.08391 (2024) - Ravid Shwartz-Ziv, Micah Goldblum, Arpit Bansal, C. Bayan Bruss, Yann LeCun, Andrew Gordon Wilson:
Just How Flexible are Neural Networks in Practice? CoRR abs/2406.11463 (2024) - Sanae Lotfi, Yilun Kuang, Brandon Amos, Micah Goldblum, Marc Finzi, Andrew Gordon Wilson:
Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models. CoRR abs/2407.18158 (2024) - Morgane Rivière, Shreya Pathak, Pier Giuseppe Sessa, Cassidy Hardin, Surya Bhupatiraju, Léonard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ramé, Johan Ferret, Peter Liu, Pouya Tafti, Abe Friesen, Michelle Casbon, Sabela Ramos, Ravin Kumar, Charline Le Lan, Sammy Jerome, Anton Tsitsulin, Nino Vieillard, Piotr Stanczyk, Sertan Girgin, Nikola Momchev, Matt Hoffman, Shantanu Thakoor, Jean-Bastien Grill, Behnam Neyshabur, Olivier Bachem, Alanna Walton, Aliaksei Severyn, Alicia Parrish, Aliya Ahmad, Allen Hutchison, Alvin Abdagic, Amanda Carl, Amy Shen, Andy Brock, Andy Coenen, Anthony Laforge, Antonia Paterson, Ben Bastian, Bilal Piot, Bo Wu, Brandon Royal, Charlie Chen, Chintu Kumar, Chris Perry, Chris Welty, Christopher A. Choquette-Choo, Danila Sinopalnikov, David Weinberger, Dimple Vijaykumar, Dominika Rogozinska, Dustin Herbison, Elisa Bandy, Emma Wang, Eric Noland, Erica Moreira, Evan Senter, Evgenii Eltyshev, Francesco Visin, Gabriel Rasskin, Gary Wei, Glenn Cameron, Gus Martins, Hadi Hashemi, Hanna Klimczak-Plucinska, Harleen Batra, Harsh Dhand, Ivan Nardini, Jacinda Mein, Jack Zhou, James Svensson, Jeff Stanway, Jetha Chan, Jin Peng Zhou, Joana Carrasqueira, Joana Iljazi, Jocelyn Becker, Joe Fernandez, Joost van Amersfoort, Josh Gordon, Josh Lipschultz, Josh Newlan, Ju-yeong Ji, Kareem Mohamed, Kartikeya Badola, Kat Black, Katie Millican, Keelin McDonell, Kelvin Nguyen, Kiranbir Sodhia, Kish Greene, Lars Lowe Sjösund, Lauren Usui, Laurent Sifre, Lena Heuermann, Leticia Lago, Lilly McNealus:
Gemma 2: Improving Open Language Models at a Practical Size. CoRR abs/2408.00118 (2024)
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