Zobrazeno 1 - 10
of 2 660
pro vyhledávání: '"Zador P"'
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 Trans. Information Theory 48 (2002), 3138-3140
We consider Zador's asymptotic formula for the distortion-rate function for a variable-rate vector quantizer in the high-rate case. This formula involves the differential entropy of the source, the rate of the quantizer in bits per sample, and a coef
Externí odkaz:
http://arxiv.org/abs/math/0207146
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:
Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract Neurons in the cortex are heterogeneous, sending diverse axonal projections to multiple brain regions. Unraveling the logic of these projections requires single-neuron resolution. Although a growing number of techniques have enabled high-thr
Externí odkaz:
https://doaj.org/article/13466c4f8e3c42dea4e075a1fbeada1d
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
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