Zobrazeno 1 - 10
of 2 246
pro vyhledávání: '"Zador, A."'
Autor:
Yuan, Eric C. -Y., Kumar, Anup, Guan, Xingyi, Hermes, Eric D., Rosen, Andrew S., Zádor, Judit, Head-Gordon, Teresa, Blau, Samuel M.
Identifying transition states -- saddle points on the potential energy surface connecting reactant and product minima -- is central to predicting kinetic barriers and understanding chemical reaction mechanisms. In this work, we train an equivariant n
Externí odkaz:
http://arxiv.org/abs/2405.02247
Publikováno v:
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Detroit, MI, USA, 2023, pp. 3358-3365
Re-localizing a camera from a single image in a previously mapped area is vital for many computer vision applications in robotics and augmented/virtual reality. In this work, we address the problem of estimating the 6 DoF camera pose relative to a gl
Externí odkaz:
http://arxiv.org/abs/2312.00500
Autor:
Devereux, Christian, Yang, Yoona, Martí, Carles, Zádor, Judit, Eldred, Michael S., Najm, Habib N.
Machine learned chemical potentials have shown great promise as alternatives to conventional computational chemistry methods to represent the potential energy of a given atomic or molecular system as a function of its geometry. However, such potentia
Externí odkaz:
http://arxiv.org/abs/2311.07910
Autor:
Pataki, Zador, Altillawi, Mohammad, Kanakis, Menelaos, Pautrat, Rémi, Shen, Fengyi, Liu, Ziyuan, Van Gool, Luc, Pollefeys, Marc
Modern learning-based visual feature extraction networks perform well in intra-domain localization, however, their performance significantly declines when image pairs are captured across long-term visual domain variations, such as different seasonal
Externí odkaz:
http://arxiv.org/abs/2311.03345
Autor:
Barabási, Dániel L, Bianconi, Ginestra, Bullmore, Ed, Burgess, Mark, Chung, SueYeon, Eliassi-Rad, Tina, George, Dileep, Kovács, István A., Makse, Hernán, Papadimitriou, Christos, Nichols, Thomas E., Sporns, Olaf, Stachenfeld, Kim, Toroczkai, Zoltán, Towlson, Emma K., Zador, Anthony M, Zeng, Hongkui, Barabási, Albert-László, Bernard, Amy, Buzsáki, György
The brain is a complex system comprising a myriad of interacting elements, posing significant challenges in understanding its structure, function, and dynamics. Network science has emerged as a powerful tool for studying such intricate systems, offer
Externí odkaz:
http://arxiv.org/abs/2305.06160
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Due to the lack of training labels and the difficulty of annotating, dealing with adverse driving conditions such as nighttime has posed a huge challenge to the perception system of autonomous vehicles. Therefore, adapting knowledge from a labelled d
Externí odkaz:
http://arxiv.org/abs/2211.11870
Autor:
Zador, Anthony, Escola, Sean, Richards, Blake, Ölveczky, Bence, Bengio, Yoshua, Boahen, Kwabena, Botvinick, Matthew, Chklovskii, Dmitri, Churchland, Anne, Clopath, Claudia, DiCarlo, James, Ganguli, Surya, Hawkins, Jeff, Koerding, Konrad, Koulakov, Alexei, LeCun, Yann, Lillicrap, Timothy, Marblestone, Adam, Olshausen, Bruno, Pouget, Alexandre, Savin, Cristina, Sejnowski, Terrence, Simoncelli, Eero, Solla, Sara, Sussillo, David, Tolias, Andreas S., Tsao, Doris
Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test, which c
Externí odkaz:
http://arxiv.org/abs/2210.08340
Autor:
Richard Zhiming Fu, Oliver Cottrell, Luisa Cutillo, Andrew Rowntree, Zsolt Zador, Heiko Wurdak, Nancy Papalopulu, Elli Marinopoulou
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Quiescence, a reversible state of cell-cycle arrest, is an important state during both normal development and cancer progression. For example, in glioblastoma (GBM) quiescent glioblastoma stem cells (GSCs) play an important role in re-establ
Externí odkaz:
https://doaj.org/article/56dfffda789b46aeb5080b706c1a7b7b
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Traumatic brain injury (TBI) is a complex condition where heterogeneity impedes the advancement of care. Understanding the diverse presentations of TBI is crucial for personalized medicine. Our study aimed to identify clinically relevant pat
Externí odkaz:
https://doaj.org/article/35e7869dfcc84264b833c936bdcc0cd8
Artificial neural networks for motor control usually adopt generic architectures like fully connected MLPs. While general, these tabula rasa architectures rely on large amounts of experience to learn, are not easily transferable to new bodies, and ha
Externí odkaz:
http://arxiv.org/abs/2201.05242