Zobrazeno 1 - 10
of 9 126
pro vyhledávání: '"P CHAKRAVARTY"'
Publikováno v:
Indian Journal of Animal Sciences, Vol 88, Iss 4 (2023)
Externí odkaz:
https://doaj.org/article/b9562838b4b84557bc6b380a28dc39d1
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
Publikováno v:
Indian Journal of Animal Sciences, Vol 92, Iss 1 (2022)
An experiment was carried out at ICAR-NRC on Yak farm using 20 male yak calves of uniform age (12–13 months) and body weight (130.7 kg). The animals were randomly divided into four groups, viz. G1, G2, G3 and G4 each having five calves. Group
Externí odkaz:
https://doaj.org/article/a3edcf18bcfc4ed5b102b19dce024aff
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:
D MEDHI, EYASHIN ALI, L C CHOUDHURY, K K BARUAH, SANTRA A, SWATI DUBEY, PAYAL AGARWAL, P CHAKRAVARTY
Publikováno v:
Indian Journal of Animal Sciences, Vol 91, Iss 12 (2022)
To utilize the plant nutrients efficiently, rumen microbes play a great role in the livestock, acting as a source of energy. Like other ruminants, the yak rumen harbours different microorganisms that are responsible for bioconversion of nutrients int
Externí odkaz:
https://doaj.org/article/50d5c53928744a82b810b1d6ff363473