Zobrazeno 1 - 10
of 3 072
pro vyhledávání: '"Anandkumar, A."'
Autor:
Gupta, Arushi, Kocielnik, Rafal, Wang, Jiayun, Nasriddinov, Firdavs, Yang, Cherine, Wong, Elyssa, Anandkumar, Anima, Hung, Andrew
During surgical training, real-time feedback from trainers to trainees is important for preventing errors and enhancing long-term skill acquisition. Accurately predicting the effectiveness of this feedback, specifically whether it leads to a change i
Externí odkaz:
http://arxiv.org/abs/2411.10919
Autor:
John, Peter St., Lin, Dejun, Binder, Polina, Greaves, Malcolm, Shah, Vega, John, John St., Lange, Adrian, Hsu, Patrick, Illango, Rajesh, Ramanathan, Arvind, Anandkumar, Anima, Brookes, David H, Busia, Akosua, Mahajan, Abhishaike, Malina, Stephen, Prasad, Neha, Sinai, Sam, Edwards, Lindsay, Gaudelet, Thomas, Regep, Cristian, Steinegger, Martin, Rost, Burkhard, Brace, Alexander, Hippe, Kyle, Naef, Luca, Kamata, Keisuke, Armstrong, George, Boyd, Kevin, Cao, Zhonglin, Chou, Han-Yi, Chu, Simon, Costa, Allan dos Santos, Darabi, Sajad, Dawson, Eric, Didi, Kieran, Fu, Cong, Geiger, Mario, Gill, Michelle, Hsu, Darren, Kaushik, Gagan, Korshunova, Maria, Kothen-Hill, Steven, Lee, Youhan, Liu, Meng, Livne, Micha, McClure, Zachary, Mitchell, Jonathan, Moradzadeh, Alireza, Mosafi, Ohad, Nashed, Youssef, Paliwal, Saee, Peng, Yuxing, Rabhi, Sara, Ramezanghorbani, Farhad, Reidenbach, Danny, Ricketts, Camir, Roland, Brian, Shah, Kushal, Shimko, Tyler, Sirelkhatim, Hassan, Srinivasan, Savitha, Stern, Abraham C, Toczydlowska, Dorota, Veccham, Srimukh Prasad, Venanzi, Niccolò Alberto Elia, Vorontsov, Anton, Wilber, Jared, Wilkinson, Isabel, Wong, Wei Jing, Xue, Eva, Ye, Cory, Yu, Xin, Zhang, Yang, Zhou, Guoqing, Zandstein, Becca, Dallago, Christian, Trentini, Bruno, Kucukbenli, Emine, Rvachov, Timur, Calleja, Eddie, Israeli, Johnny, Clifford, Harry, Haukioja, Risto, Haemel, Nicholas, Tretina, Kyle, Tadimeti, Neha, Costa, Anthony B
Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increasingly relies on computational scale, with recent protein language mode
Externí odkaz:
http://arxiv.org/abs/2411.10548
Autor:
Chakraborty, Abhishek, Patti, Taylor L., Khailany, Brucek, Jordan, Andrew N., Anandkumar, Anima
Effective Hamiltonian calculations for large quantum systems can be both analytically intractable and numerically expensive using standard techniques. In this manuscript, we present numerical techniques inspired by Nonperturbative Analytical Diagonal
Externí odkaz:
http://arxiv.org/abs/2411.09982
Autor:
Agarwal, Ishita, Patti, Taylor L., Bravo, Rodrigo Araiza, Yelin, Susanne F., Anandkumar, Anima
Quantum Neuromorphic Computing (QNC) merges quantum computation with neural computation to create scalable, noise-resilient algorithms for quantum machine learning (QML). At the core of QNC is the quantum perceptron (QP), which leverages the analog d
Externí odkaz:
http://arxiv.org/abs/2411.09093
Autor:
Li, Zhuofang, Kocielnik, Rafal, Linegar, Mitchell, Sambrano, Deshawn, Soltani, Fereshteh, Kim, Min, Naqvie, Nabiha, Cahill, Grant, Anandkumar, Animashree, Alvarez, R. Michael
Online competitive action games have flourished as a space for entertainment and social connections, yet they face challenges from a small percentage of players engaging in disruptive behaviors. This study delves into the under-explored realm of unde
Externí odkaz:
http://arxiv.org/abs/2411.01057
Autor:
Kumarappan, Adarsh, Tiwari, Mo, Song, Peiyang, George, Robert Joseph, Xiao, Chaowei, Anandkumar, Anima
Large Language Models (LLMs) have been successful in mathematical reasoning tasks such as formal theorem proving when integrated with interactive proof assistants like Lean. Existing approaches involve training or fine-tuning an LLM on a specific dat
Externí odkaz:
http://arxiv.org/abs/2410.06209
Autor:
Jatyani, Armeet Singh, Wang, Jiayun, Wu, Zihui, Liu-Schiaffini, Miguel, Tolooshams, Bahareh, Anandkumar, Anima
Compressed Sensing MRI (CS-MRI) reconstructs images of the body's internal anatomy from undersampled and compressed measurements, thereby reducing scan times and minimizing the duration patients need to remain still. Recently, deep neural networks ha
Externí odkaz:
http://arxiv.org/abs/2410.16290
Recent advancements in diffusion models have been effective in learning data priors for solving inverse problems. They leverage diffusion sampling steps for inducing a data prior while using a measurement guidance gradient at each step to impose data
Externí odkaz:
http://arxiv.org/abs/2410.03463
Autor:
Ding, Mucong, Deng, Chenghao, Choo, Jocelyn, Wu, Zichu, Agrawal, Aakriti, Schwarzschild, Avi, Zhou, Tianyi, Goldstein, Tom, Langford, John, Anandkumar, Anima, Huang, Furong
While generalization over tasks from easy to hard is crucial to profile language models (LLMs), the datasets with fine-grained difficulty annotations for each problem across a broad range of complexity are still blank. Aiming to address this limitati
Externí odkaz:
http://arxiv.org/abs/2409.18433
Autor:
Liu, Shengchao, Yan, Divin, Du, Weitao, Liu, Weiyang, Li, Zhuoxinran, Guo, Hongyu, Borgs, Christian, Chayes, Jennifer, Anandkumar, Anima
Artificial intelligence models have shown great potential in structure-based drug design, generating ligands with high binding affinities. However, existing models have often overlooked a crucial physical constraint: atoms must maintain a minimum pai
Externí odkaz:
http://arxiv.org/abs/2409.10584