Zobrazeno 1 - 10
of 39 662
pro vyhledávání: '"A. Modi"'
Autor:
Cai, Diana, Modi, Chirag, Margossian, Charles C., Gower, Robert M., Blei, David M., Saul, Lawrence K.
We develop EigenVI, an eigenvalue-based approach for black-box variational inference (BBVI). EigenVI constructs its variational approximations from orthogonal function expansions. For distributions over $\mathbb{R}^D$, the lowest order term in these
Externí odkaz:
http://arxiv.org/abs/2410.24054
The realization of fault-tolerant quantum computers hinges on effective quantum error correction protocols, whose performance significantly relies on the nature of the underlying noise. In this work, we directly study the structure of non-Markovian c
Externí odkaz:
http://arxiv.org/abs/2410.23779
Black-box variational inference (BBVI) scales poorly to high dimensional problems when it is used to estimate a multivariate Gaussian approximation with a full covariance matrix. In this paper, we extend the batch-and-match (BaM) framework for score-
Externí odkaz:
http://arxiv.org/abs/2410.22292
Autor:
Modi, Chirag
Hamiltonian Monte-Carlo (HMC) and its auto-tuned variant, the No U-Turn Sampler (NUTS) can struggle to accurately sample distributions with complex geometries, e.g., varying curvature, due to their constant step size for leapfrog integration and fixe
Externí odkaz:
http://arxiv.org/abs/2410.21587
Autor:
Modi, Rajat, Rawat, Yogesh Singh
In this work, we propose Asynchronous Perception Machine (APM), a computationally-efficient architecture for test-time-training (TTT). APM can process patches of an image one at a time in any order \textit{asymmetrically,} and \textit{still encode} s
Externí odkaz:
http://arxiv.org/abs/2410.20535
This paper explores the impact of occlusions in video action detection. We facilitate this study by introducing five new benchmark datasets namely O-UCF and O-JHMDB consisting of synthetically controlled static/dynamic occlusions, OVIS-UCF and OVIS-J
Externí odkaz:
http://arxiv.org/abs/2410.19553
Autor:
Bavishi, Shrey, Modi, Shrey
The escalating frequency and scale of recent malware attacks underscore the urgent need for swift and precise malware classification in the ever-evolving cybersecurity landscape. Key challenges include accurately categorizing closely related malware
Externí odkaz:
http://arxiv.org/abs/2409.19461
Autor:
Xu, Justin, Chen, Zhihong, Johnston, Andrew, Blankemeier, Louis, Varma, Maya, Hom, Jason, Collins, William J., Modi, Ankit, Lloyd, Robert, Hopkins, Benjamin, Langlotz, Curtis, Delbrouck, Jean-Benoit
Publikováno v:
Proceedings of the 23rd Workshop on Biomedical Natural Language Processing (2024) 85-98
Recent developments in natural language generation have tremendous implications for healthcare. For instance, state-of-the-art systems could automate the generation of sections in clinical reports to alleviate physician workload and streamline hospit
Externí odkaz:
http://arxiv.org/abs/2409.16603
We develop a transformer-based conditional generative model for discrete point objects and their properties. We use it to build a model for populating cosmological simulations with gravitationally collapsed structures called dark matter halos. Specif
Externí odkaz:
http://arxiv.org/abs/2409.11401
Autor:
Pandey, Shivam, Modi, Chirag, Wandelt, Benjamin D., Bartlett, Deaglan J., Bayer, Adrian E., Bryan, Greg L., Ho, Matthew, Lavaux, Guilhem, Makinen, T. Lucas, Villaescusa-Navarro, Francisco
To maximize the amount of information extracted from cosmological datasets, simulations that accurately represent these observations are necessary. However, traditional simulations that evolve particles under gravity by estimating particle-particle i
Externí odkaz:
http://arxiv.org/abs/2409.09124