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- David Eisenstat
- David S. Eisenberg
University of California, Los Angeles, CA, USA - David Eisenberg
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- Andrew David Eisenberg
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Publication search results
found 400 matches
- 2025
- Simon Bin Akter, Sumya Akter, Moon Das Tuli, David Eisenberg, Aaron Lotvola, Humayera Islam, Jorge Eduardo Fresneda Fernandez, Maik Hüttemann, Tanmoy Sarkar Pias:
Fair and explainable Myocardial Infarction (MI) prediction: Novel strategies for feature selection and class imbalance correction. Comput. Biol. Medicine 184: 109413 (2025) - Simon Bin Akter
, Sumya Akter
, Rakibul Hasan
, Md. Mahadi Hasan
, A. M. Tayeful Islam
, Tanmoy Sarkar Pias
, Jorge Eduardo Fresneda Fernandez
, Md. Golam Rabiul Alam
, David Eisenberg
:
Early detection of subjective cognitive decline from self-reported symptoms: An interpretable attention-cost fusion approach. J. Biomed. Informatics 162: 104770 (2025) - Helia Hashemi, Jason Eisner, Corby Rosset, Benjamin Van Durme, Chris Kedzie:
LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts. CoRR abs/2501.00274 (2025) - 2024
- Martin Eisenberg
, Apurvanand Sahay
, Davide Di Ruscio, Ludovico Iovino
, Manuel Wimmer, Alfonso Pierantonio
:
Multi-objective model transformation chain exploration with MOMoT. Inf. Softw. Technol. 174: 107500 (2024) - Fengling Li, Suzanne Ackloo, Cheryl H. Arrowsmith, Fuqiang Ban, Christopher J. Barden, Hartmut Beck, Jan Beránek, Francois Berenger, Albina Bolotokova, Guillaume Bret, Marko Breznik, Emanuele Carosati, Irene Chau, Yu Chen, Artem Cherkasov, Dennis Della Corte, Katrin Denzinger, Aiping Dong, Sorin Draga, Ian Dunn, Kristina Edfeldt, Aled M. Edwards, Merveille K. I. Eguida, Paul Eisenhuth, Lukas Friedrich, Alexander Fuerll, Spencer S. Gardiner, Francesco Gentile, Pegah Ghiabi, Elisa Gibson, Marta Glavatskikh, Christoph Gorgulla, Judith Guenther, Anders Gunnarsson, Filipp Gusev, Evgeny Gutkin, Levon Halabelian, Rachel J. Harding, Alexander Hillisch, Laurent Hoffer, Anders Hogner, Scott Houliston, John J. Irwin, Olexandr Isayev, Aleksandra Ivanova, Célien Jacquemard, Austin J. Jarrett, Jan H. Jensen, Dmitri Kireev, Julian Kleber, S. Benjamin Koby, David Koes, Ashutosh Kumar, Maria G. Kurnikova, Alina Kutlushina, Uta F. Lessel, Fabian Liessmann, Sijie Liu, Wei Lu, Jens Meiler, Akhila Mettu, Guzel Minibaeva, Rocco Moretti, Connor J. Morris, Chamali Narangoda, Theresa Noonan, Leon Obendorf, Szymon Pach, Amit Pandit, Sumera Perveen, Gennady Poda, Pavel G. Polishchuk, Kristina Puls, Vera Pütter, Didier Rognan, Dylan Roskams-Edris, Christina E. M. Schindler, François Sindt, Vojtech Spiwok, Casper Steinmann, Rick L. Stevens, Valerij Talagayev, Damon Tingey, Oanh Vu, W. Patrick Walters, Xiaowen Wang, Zhenyu Wang, Gerhard Wolber, Clemens Alexander Wolf, Lars Wortmann, Hong Zeng, Carlos A. Zepeda, Kam Y. J. Zhang, Jixian Zhang, Shuangjia Zheng, Matthieu Schapira:
CACHE Challenge #1: Targeting the WDR Domain of LRRK2, A Parkinson's Disease Associated Protein. J. Chem. Inf. Model. 64(22): 8521-8536 (2024) - Kunle Sunday Oguntoye
, Simon Laflamme
, Roy E. Sturgill
, Daniel A. Salazar Martinez, David J. Eisenmann, Anne Kimber
:
Probabilistic Method to Fuse Artificial Intelligence-Generated Underground Utility Mapping. Sensors 24(11): 3559 (2024) - Sky CH-Wang, Benjamin Van Durme, Jason Eisner, Chris Kedzie:
Do Androids Know They're Only Dreaming of Electric Sheep? ACL (Findings) 2024: 4401-4420 - Helia Hashemi, Jason Eisner, Corby Rosset, Benjamin Van Durme, Chris Kedzie:
LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts. ACL (1) 2024: 13806-13834 - Boshi Wang, Hao Fang, Jason Eisner, Benjamin Van Durme, Yu Su:
LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error. ACL (1) 2024: 10583-10604 - Swati Mishra
, Matt Ryerkerk
, Yitzchak Lockerman
, David Eis
, Jeffrey M. Rzeszotarski
:
Teachable Facets: A Framework of Interactive Machine Teaching for Information Filtering. CHIIR 2024: 178-188 - Kaj Bostrom, Harsh Jhamtani, Hao Fang, Sam Thomson, Richard Shin, Patrick Xia, Benjamin Van Durme, Jason Eisner, Jacob Andreas:
Language-to-Code Translation with a Single Labeled Example. EMNLP 2024: 8101-8112 - Yunmo Chen, Tongfei Chen, Harsh Jhamtani, Patrick Xia, Richard Shin, Jason Eisner, Benjamin Van Durme:
Learning to Retrieve Iteratively for In-Context Learning. EMNLP 2024: 7156-7168 - Michael Gerstenberger, Mykyta Kovalenko, David Przewozny, Jannes Magnusson, Eike Gassen, Jakub Pawlak, Jochen Hirth, Laura von Hirschhausen, Detlef Runde, Anna Hilsmann, Peter Eisert, Sebastian Bosse:
Automatisierte Frucht- und Pflanzenerkennung in Apfelplantagen durch künstliche Intelligenz. GIL 2024: 59-70 - David Eisenberg, Tanmoy Sarkar Pias, Jorge E. Fresneda, Jerry Fjermestad:
Neuromarketing Techniques to Enhance Consumer Preference Prediction. HICSS 2024: 923-932 - Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerík, Jonathan Scholz, David Held:
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks. ICLR 2024 - Vernon S. Crasto, William R. Eisenstadt, David P. Arnold:
Wirelessly Powered Buried Soil Moisture Sensor System. IEEE SENSORS 2024: 1-4 - Nikita Moghe, Patrick Xia, Jacob Andreas, Jason Eisner, Benjamin Van Durme, Harsh Jhamtani:
Interpreting User Requests in the Context of Natural Language Standing Instructions. NAACL-HLT (Findings) 2024: 4043-4060 - Mohammad Nomaan Qureshi, Ben Eisner, David Held:
On Time-Indexing as Inductive Bias in Deep RL for Sequential Manipulation Tasks. CoRR abs/2401.01993 (2024) - Boshi Wang, Hao Fang, Jason Eisner, Benjamin Van Durme, Yu Su:
LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error. CoRR abs/2403.04746 (2024) - Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, Victor Akinwande, Namir Al-Nuaimi, Najla Alfaraj, Elie Alhajjar, Lora Aroyo, Trupti Bavalatti, Borhane Blili-Hamelin, Kurt D. Bollacker, Rishi Bomassani, Marisa Ferrara Boston, Siméon Campos, Kal Chakra, Canyu Chen, Cody Coleman, Zacharie Delpierre Coudert, Leon Derczynski, Debojyoti Dutta, Ian Eisenberg, James Ezick, Heather Frase, Brian Fuller, Ram Gandikota, Agasthya Gangavarapu, Ananya Gangavarapu, James Gealy, Rajat Ghosh, James Goel, Usman Gohar, Subhra S. Goswami, Scott A. Hale, Wiebke Hutiri, Joseph Marvin Imperial, Surgan Jandial, Nick Judd
, Felix Juefei-Xu, Foutse Khomh, Bhavya Kailkhura, Hannah Rose Kirk, Kevin Klyman, Chris Knotz, Michael Kuchnik, Shachi H. Kumar, Chris Lengerich, Bo Li, Zeyi Liao, Eileen Peters Long, Victor Lu, Yifan Mai, Priyanka Mary Mammen, Kelvin Manyeki, Sean McGregor, Virendra Mehta, Shafee Mohammed, Emanuel Moss, Lama Nachman, Dinesh Jinenhally Naganna, Amin Nikanjam, Besmira Nushi, Luis Oala, Iftach Orr, Alicia Parrish, Cigdem Patlak, William Pietri, Forough Poursabzi-Sangdeh, Eleonora Presani, Fabrizio Puletti, Paul Röttger, Saurav Sahay, Tim Santos, Nino Scherrer, Alice Schoenauer Sebag, Patrick Schramowski, Abolfazl Shahbazi, Vin Sharma, Xudong Shen, Vamsi Sistla, Leonard Tang, Davide Testuggine, Vithursan Thangarasa, Elizabeth Anne Watkins, Rebecca Weiss, Chris Welty, Tyler Wilbers, Adina Williams, Carole-Jean Wu, Poonam Yadav, Xianjun Yang, Yi Zeng, Wenhui Zhang, Fedor Zhdanov, Jiacheng Zhu, Percy Liang, Peter Mattson, Joaquin Vanschoren:
Introducing v0.5 of the AI Safety Benchmark from MLCommons. CoRR abs/2404.12241 (2024) - Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerík, Jonathan Scholz, David Held:
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks. CoRR abs/2404.13478 (2024) - Leon Eisemann, Mirjam Fehling-Kaschek, Henrik Gommel, David Hermann, Marvin Klemp, Martin Lauer, Benjamin Lickert, Florian Lüttner, Robin Moss, Nicole Neis, Maria Pohle, Simon Romanski, Daniel Stadler, Alexander Stolz, Jens R. Ziehn, Jingxing Zhou:
An Approach to Systematic Data Acquisition and Data-Driven Simulation for the Safety Testing of Automated Driving Functions. CoRR abs/2405.01776 (2024) - Leon Eisemann, Mirjam Fehling-Kaschek, Silke Forkert, Andreas Forster, Henrik Gommel, Susanne Guenther, Stephan Hammer, David Hermann, Marvin Klemp, Benjamin Lickert, Florian Lüttner, Robin Moss, Nicole Neis, Maria Pohle, Dominik Schreiber, Cathrina Sowa, Daniel Stadler, Janina Stompe, Michael Strobelt, David Unger, Jens R. Ziehn:
A Joint Approach Towards Data-Driven Virtual Testing for Automated Driving: The AVEAS Project. CoRR abs/2405.06286 (2024) - Valentina Tardugno Poleo, Nora Eisner, David W. Hogg:
NotPlaNET: Removing False Positives from Planet Hunters TESS with Machine Learning. CoRR abs/2405.18278 (2024) - Yunmo Chen, Tongfei Chen, Harsh Jhamtani, Patrick Xia, Richard Shin, Jason Eisner, Benjamin Van Durme:
Learning to Retrieve Iteratively for In-Context Learning. CoRR abs/2406.14739 (2024) - David Pape, Thorsten Eisenhofer, Lea Schönherr:
Prompt Obfuscation for Large Language Models. CoRR abs/2409.11026 (2024) - Yishu Li, Wen Hui Leng, Yiming Fang, Ben Eisner, David Held:
FlowBotHD: History-Aware Diffuser Handling Ambiguities in Articulated Objects Manipulation. CoRR abs/2410.07078 (2024) - Gunter Bombaerts, Tom Hannes, Martin Adam, Alessandra Aloisi, Joel Anderson, Lawrence Berger, Stefano Davide Bettera, Enrico Campo, Laura Candiotto, Silvia Caprioglio Panizza, Yves Citton, Diego D'Angelo, Matthew Dennis, Nathalie Depraz, Peter Doran, Wolfgang Drechsler, Bill Duane, William Edelglass, Iris Eisenberger, Beverley Foulks McGuire, Antony Fredriksson, Karamjit S. Gill, Peter D. Hershock, Soraj Hongladarom, Beth Jacobs, Gábor Karsai, Thomas Lennerfors, Jeanne Lim, Chien-Te Lin, Mark Losoncz, David Loy, Lavinia Marin, Bence Péter Marosán, Chiara Mascarello, David McMahan, Jin Y. Park, Nina Petek, Anna Puzio, Katrien Schaubroek, Jens Schlieter, Brian Schroeder, Shobhit Shakya, Juewei Shi, Elizaveta Solomonova, Francesco Tormen, Jitendra Uttam, Marieke Van Vugt, Sebastjan Vörös, Maren Wehrle, Galit Wellner, Jason M. Wirth, Olaf Witkowski, Apiradee Wongkitrungrueng, Dale S. Wright, Yutong Zheng:
From an attention economy to an ecology of attending. A manifesto. CoRR abs/2410.17421 (2024) - Eric Cai, Octavian Donca, Ben Eisner, David Held:
Non-rigid Relative Placement through 3D Dense Diffusion. CoRR abs/2410.19247 (2024) - Shangdi Yu, Jessica Shi, Jamison Meindl, David Eisenstat, Xiaoen Ju, Sasan Tavakkol, Laxman Dhulipala, Jakub Lacki, Vahab Mirrokni, Julian Shun:
The ParClusterers Benchmark Suite (PCBS): A Fine-Grained Analysis of Scalable Graph Clustering. CoRR abs/2411.10290 (2024)
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retrieved on 2025-02-16 03:44 CET from data curated by the dblp team
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