Zobrazeno 1 - 10
of 2 268
pro vyhledávání: '"JOSHI, P. K."'
Autor:
Prasad, Radhika, Wanare, Sanjana, Karan, Suman, Joshi, Mritunjay K., Bhattacharjee, Abhinandan, Jha, Anand K.
Publikováno v:
Physical Review Applied Vol 22, Issue 6, 10 December, 2024
Structured optical fields have led to several ground-breaking techniques in classical imaging and microscopy. At the same time, in the quantum domain, position-momentum entangled photon fields have been shown to have several unique features that can
Externí odkaz:
http://arxiv.org/abs/2412.10954
Autor:
Bakshi, Gargi, Joshi, Rushikesh K.
Dynamic changes in processes necessitate the notion of state equivalence between the old and new workflows. In several cases, the history of the workflow to be migrated provides sufficient context for a meaningful migration. In this paper, we present
Externí odkaz:
http://arxiv.org/abs/2412.08314
Autor:
Jamasb, Arian R., Morehead, Alex, Joshi, Chaitanya K., Zhang, Zuobai, Didi, Kieran, Mathis, Simon V., Harris, Charles, Tang, Jian, Cheng, Jianlin, Lio, Pietro, Blundell, Tom L.
We introduce ProteinWorkshop, a comprehensive benchmark suite for representation learning on protein structures with Geometric Graph Neural Networks. We consider large-scale pre-training and downstream tasks on both experimental and predicted structu
Externí odkaz:
http://arxiv.org/abs/2406.13864
Autor:
Anand, Rishabh, Joshi, Chaitanya K., Morehead, Alex, Jamasb, Arian R., Harris, Charles, Mathis, Simon V., Didi, Kieran, Hooi, Bryan, Liò, Pietro
We introduce RNA-FrameFlow, the first generative model for 3D RNA backbone design. We build upon SE(3) flow matching for protein backbone generation and establish protocols for data preparation and evaluation to address unique challenges posed by RNA
Externí odkaz:
http://arxiv.org/abs/2406.13839
The oscillating magnetic field produced by unbalanced currents in radio-frequency ion traps induces transition frequency shifts and sideband transitions that can be harmful to precision spectroscopy experiments. Here, we describe a methodology, based
Externí odkaz:
http://arxiv.org/abs/2405.18883
Autor:
Lawrence, Elsa, El-Shazly, Adham, Seal, Srijit, Joshi, Chaitanya K, Liò, Pietro, Singh, Shantanu, Bender, Andreas, Sormanni, Pietro, Greenig, Matthew
Modern life sciences research is increasingly relying on artificial intelligence approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in l
Externí odkaz:
http://arxiv.org/abs/2403.04106
Autor:
Joshi, Lata Kh, Franke, Johannes, Rath, Aniket, Ares, Filiberto, Murciano, Sara, Kranzl, Florian, Blatt, Rainer, Zoller, Peter, Vermersch, Benoît, Calabrese, Pasquale, Roos, Christian F., Joshi, Manoj K.
Publikováno v:
Phys. Rev. Lett. 133, 010402, 2024
The non-equilibrium physics of many-body quantum systems harbors various unconventional phenomena. In this study, we experimentally investigate one of the most puzzling of these phenomena -- the quantum Mpemba effect, where a tilted ferromagnet resto
Externí odkaz:
http://arxiv.org/abs/2401.04270
Autor:
Duval, Alexandre, Mathis, Simon V., Joshi, Chaitanya K., Schmidt, Victor, Miret, Santiago, Malliaros, Fragkiskos D., Cohen, Taco, Liò, Pietro, Bengio, Yoshua, Bronstein, Michael
Recent advances in computational modelling of atomic systems, spanning molecules, proteins, and materials, represent them as geometric graphs with atoms embedded as nodes in 3D Euclidean space. In these graphs, the geometric attributes transform acco
Externí odkaz:
http://arxiv.org/abs/2312.07511
Autor:
Harris, Charles, Didi, Kieran, Jamasb, Arian R., Joshi, Chaitanya K., Mathis, Simon V., Lio, Pietro, Blundell, Tom
Deep generative models for structure-based drug design (SBDD), where molecule generation is conditioned on a 3D protein pocket, have received considerable interest in recent years. These methods offer the promise of higher-quality molecule generation
Externí odkaz:
http://arxiv.org/abs/2308.07413
Autor:
Zhang, Xuan, Wang, Limei, Helwig, Jacob, Luo, Youzhi, Fu, Cong, Xie, Yaochen, Liu, Meng, Lin, Yuchao, Xu, Zhao, Yan, Keqiang, Adams, Keir, Weiler, Maurice, Li, Xiner, Fu, Tianfan, Wang, Yucheng, Yu, Haiyang, Xie, YuQing, Fu, Xiang, Strasser, Alex, Xu, Shenglong, Liu, Yi, Du, Yuanqi, Saxton, Alexandra, Ling, Hongyi, Lawrence, Hannah, Stärk, Hannes, Gui, Shurui, Edwards, Carl, Gao, Nicholas, Ladera, Adriana, Wu, Tailin, Hofgard, Elyssa F., Tehrani, Aria Mansouri, Wang, Rui, Daigavane, Ameya, Bohde, Montgomery, Kurtin, Jerry, Huang, Qian, Phung, Tuong, Xu, Minkai, Joshi, Chaitanya K., Mathis, Simon V., Azizzadenesheli, Kamyar, Fang, Ada, Aspuru-Guzik, Alán, Bekkers, Erik, Bronstein, Michael, Zitnik, Marinka, Anandkumar, Anima, Ermon, Stefano, Liò, Pietro, Yu, Rose, Günnemann, Stephan, Leskovec, Jure, Ji, Heng, Sun, Jimeng, Barzilay, Regina, Jaakkola, Tommi, Coley, Connor W., Qian, Xiaoning, Qian, Xiaofeng, Smidt, Tess, Ji, Shuiwang
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating, and enabling our understanding of natural phenomena at a wide range
Externí odkaz:
http://arxiv.org/abs/2307.08423