Zobrazeno 1 - 10
of 2 752
pro vyhledávání: '"Aspuru-Guzik A."'
Understanding is a crucial yet elusive concept in artificial intelligence (AI). This work proposes a framework for analyzing understanding based on the notion of composability. Given any subject (e.g., a person or an AI), we suggest characterizing it
Externí odkaz:
http://arxiv.org/abs/2408.08463
Autor:
Wang, Haorui, Skreta, Marta, Ser, Cher-Tian, Gao, Wenhao, Kong, Lingkai, Strieth-Kalthoff, Felix, Duan, Chenru, Zhuang, Yuchen, Yu, Yue, Zhu, Yanqiao, Du, Yuanqi, Aspuru-Guzik, Alán, Neklyudov, Kirill, Zhang, Chao
Molecular discovery, when formulated as an optimization problem, presents significant computational challenges because optimization objectives can be non-differentiable. Evolutionary Algorithms (EAs), often used to optimize black-box objectives in mo
Externí odkaz:
http://arxiv.org/abs/2406.16976
Autor:
Bellonzi, Nicole, Kunitsa, Alexander, Cantin, Joshua T., Campos-Gonzalez-Angulo, Jorge A., Radin, Maxwell D., Zhou, Yanbing, Johnson, Peter D., Martínez-Martínez, Luis A., Jangrouei, Mohammad Reza, Brahmachari, Aritra Sankar, Wang, Linjun, Patel, Smik, Kodrycka, Monika, Loaiza, Ignacio, Lang, Robert A., Aspuru-Guzik, Alán, Izmaylov, Artur F., Fontalvo, Jhonathan Romero, Cao, Yudong
The industrial manufacturing of chemicals consumes a significant amount of energy and raw materials. In principle, the development of new catalysts could greatly improve the efficiency of chemical production. However, the discovery of viable catalyst
Externí odkaz:
http://arxiv.org/abs/2406.06335
Autor:
Rolnick, David, Aspuru-Guzik, Alan, Beery, Sara, Dilkina, Bistra, Donti, Priya L., Ghassemi, Marzyeh, Kerner, Hannah, Monteleoni, Claire, Rolf, Esther, Tambe, Milind, White, Adam
As applications of machine learning proliferate, innovative algorithms inspired by specific real-world challenges have become increasingly important. Such work offers the potential for significant impact not merely in domains of application but also
Externí odkaz:
http://arxiv.org/abs/2403.17381
Visual recognition of materials and their states is essential for understanding the physical world, from identifying wet regions on surfaces or stains on fabrics to detecting infected areas on plants or minerals in rocks. Collecting data that capture
Externí odkaz:
http://arxiv.org/abs/2403.03309
We present a generative diffusion model specifically tailored to the discovery of surface structures. The generative model takes into account substrate registry and periodicity by including masked atoms and $z$-directional confinement. Using a rotati
Externí odkaz:
http://arxiv.org/abs/2402.17404
Autor:
Guo, Naixu, Yu, Zhan, Choi, Matthew, Agrawal, Aman, Nakaji, Kouhei, Aspuru-Guzik, Alán, Rebentrost, Patrick
Generative machine learning methods such as large-language models are revolutionizing the creation of text and images. While these models are powerful they also harness a large amount of computational resources. The transformer is a key component in
Externí odkaz:
http://arxiv.org/abs/2402.16714
Autor:
Vakili, Mohammad Ghazi, Gorgulla, Christoph, Nigam, AkshatKumar, Bezrukov, Dmitry, Varoli, Daniel, Aliper, Alex, Polykovsky, Daniil, Das, Krishna M. Padmanabha, Snider, Jamie, Lyakisheva, Anna, Mansob, Ardalan Hosseini, Yao, Zhong, Bitar, Lela, Radchenko, Eugene, Ding, Xiao, Liu, Jinxin, Meng, Fanye, Ren, Feng, Cao, Yudong, Stagljar, Igor, Aspuru-Guzik, Alán, Zhavoronkov, Alex
The discovery of small molecules with therapeutic potential is a long-standing challenge in chemistry and biology. Researchers have increasingly leveraged novel computational techniques to streamline the drug development process to increase hit rates
Externí odkaz:
http://arxiv.org/abs/2402.08210
Autor:
Kristiadi, Agustinus, Strieth-Kalthoff, Felix, Skreta, Marta, Poupart, Pascal, Aspuru-Guzik, Alán, Pleiss, Geoff
Automation is one of the cornerstones of contemporary material discovery. Bayesian optimization (BO) is an essential part of such workflows, enabling scientists to leverage prior domain knowledge into efficient exploration of a large molecular space.
Externí odkaz:
http://arxiv.org/abs/2402.05015
Autor:
Schleich, Philipp, Kristensen, Lasse Bjørn, Angulo, Jorge A. Campos Gonzalez, Avagliano, Davide, Bagherimehrab, Mohsen, Aldossary, Abdulrahman, Gorgulla, Christoph, Fitzsimons, Joe, Aspuru-Guzik, Alán
Simulating chemical systems is highly sought after and computationally challenging, as the simulation cost exponentially increases with the system size. Quantum computers have been proposed as a computational means to overcome this bottleneck. Most e
Externí odkaz:
http://arxiv.org/abs/2401.09268