Zobrazeno 1 - 10
of 9 230
pro vyhledávání: '"Chakravarty, P."'
In recent years, advances in artificial intelligence (AI) have transformed structural biology, particularly protein structure prediction. Though AI-based methods, such as AlphaFold (AF), often predict single conformations of proteins with high accura
Externí odkaz:
http://arxiv.org/abs/2410.14898
Autor:
Chakravarty, Arunava, Emre, Taha, Lachinov, Dmitrii, Rivail, Antoine, Scholl, Hendrik, Fritsche, Lars, Sivaprasad, Sobha, Rueckert, Daniel, Lotery, Andrew, Schmidt-Erfurth, Ursula, Bogunović, Hrvoje
Predicting future disease progression risk from medical images is challenging due to patient heterogeneity, and subtle or unknown imaging biomarkers. Moreover, deep learning (DL) methods for survival analysis are susceptible to image domain shifts ac
Externí odkaz:
http://arxiv.org/abs/2409.20195
Resource sharing is a crucial part of a multi-robot system. We propose a Boolean satisfiability based approach to resource sharing. Our key contributions are an algorithm for converting any constrained assignment to a weighted-SAT based optimization.
Externí odkaz:
http://arxiv.org/abs/2408.07942
The double-cone geometry is a saddle of the gravitational path integral, which explains the chaotic statistics of the spectrum of black hole microstates. This geometry is the usual AdS-Schwarzschild black hole, but with a periodic identification of t
Externí odkaz:
http://arxiv.org/abs/2407.04781
Entity Augmentation for Efficient Classification of Vertically Partitioned Data with Limited Overlap
Autor:
Amalanshu, Avi, Nagaswamy, Viswesh, Prudhvi, G. V. S. S., Sirvi, Yash, Chakravarty, Debashish
Vertical Federated Learning (VFL) is a machine learning paradigm for learning from vertically partitioned data (i.e. features for each input are distributed across multiple "guest" clients and an aggregating "host" server owns labels) without communi
Externí odkaz:
http://arxiv.org/abs/2406.17899
Autor:
Nevgi, Rukma, Dey, Subha, Bhattacharya, Nandana, Ershadrad, Soheil, Dan, Tinku, Chakravarty, Sujay, Kaushik, S. D., Klewe, Christoph, Sterbinsky, George E., Sanyal, Biplab, Middey, Srimanta
Understanding how local distortions determine the functional properties of high entropy materials, containing five or more elements at a crystallographic site, is an open challenge. We address this for a compositionally complex spinel oxide (Mn$_{0.2
Externí odkaz:
http://arxiv.org/abs/2406.01156
Autor:
Emre, Taha, Chakravarty, Arunava, Lachinov, Dmitrii, Rivail, Antoine, Schmidt-Erfurth, Ursula, Bogunović, Hrvoje
Contrastive pretraining provides robust representations by ensuring their invariance to different image transformations while simultaneously preventing representational collapse. Equivariant contrastive learning, on the other hand, provides represent
Externí odkaz:
http://arxiv.org/abs/2405.09404
Autor:
Chakravarty, Aditya
Recent transformer-based ASR models have achieved word-error rates (WER) below 4%, surpassing human annotator accuracy, yet they demand extensive server resources, contributing to significant carbon footprints. The traditional server-based architectu
Externí odkaz:
http://arxiv.org/abs/2405.01004
Autor:
Chakravarty, Joydeep, Dasgupta, Keshav
Publikováno v:
JHEP 10 (2024) 065
We propose precise effective field theory criteria to obtain a four-dimensional de Sitter space within M-theory. To this effect, starting with the state space described by the action of metric perturbations, fluxes etc over the supersymmetric Minkows
Externí odkaz:
http://arxiv.org/abs/2404.11680
Autor:
Chakravarty, Sayok, Spanier, Nicholas
We analyze a random greedy process to construct $q$-uniform linear hypergraphs using the differential equation method. We show for $q=o(\sqrt{\log n})$, that this process yields a hypergraph with $\frac{n(n-1)}{q(q-1)}(1-o(1))$ edges. We also give so
Externí odkaz:
http://arxiv.org/abs/2404.01452