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pro vyhledávání: '"MAJUMDER, A."'
Autor:
Li, Hao, Lal, Shamit, Li, Zhiheng, Xie, Yusheng, Wang, Ying, Zou, Yang, Majumder, Orchid, Manmatha, R., Tu, Zhuowen, Ermon, Stefano, Soatto, Stefano, Swaminathan, Ashwin
We empirically study the scaling properties of various Diffusion Transformers (DiTs) for text-to-image generation by performing extensive and rigorous ablations, including training scaled DiTs ranging from 0.3B upto 8B parameters on datasets up to 60
Externí odkaz:
http://arxiv.org/abs/2412.12391
Publikováno v:
Transactions on Machine Learning Research - 2024
Previous studies have demonstrated that not each sample in a dataset is of equal importance during training. Data pruning aims to remove less important or informative samples while still achieving comparable results as training on the original (untru
Externí odkaz:
http://arxiv.org/abs/2412.10091
Autor:
Majumder, Reek, Comert, Gurcan, Werth, David, Gale, Adrian, Chowdhury, Mashrur, Salek, M Sabbir
The network of services, including delivery, farming, and environmental monitoring, has experienced exponential expansion in the past decade with Unmanned Aerial Vehicles (UAVs). Yet, UAVs are not robust enough against cyberattacks, especially on the
Externí odkaz:
http://arxiv.org/abs/2412.02539
Global Climate Models (GCMs) are numerical models that simulate complex physical processes within the Earth's climate system and are essential for understanding and predicting climate change. However, GCMs suffer from systemic biases due to simplific
Externí odkaz:
http://arxiv.org/abs/2411.18799
Given a multi-view video, which viewpoint is most informative for a human observer? Existing methods rely on heuristics or expensive ``best-view" supervision to answer this question, limiting their applicability. We propose a weakly supervised approa
Externí odkaz:
http://arxiv.org/abs/2411.08753
We theoretically explore the spin texture dynamics of a harmonically trapped spin-1 Bose-Einstein condensate with Rashba spin-orbit coupling and ferromagnetic spin-exchange interactions under a sinusoidally varying magnetic field along the $x$-direct
Externí odkaz:
http://arxiv.org/abs/2411.07204
Gaussian processes (GPs) are a ubiquitous tool for geostatistical modeling with high levels of flexibility and interpretability, and the ability to make predictions at unseen spatial locations through a process called Kriging. Estimation of Kriging w
Externí odkaz:
http://arxiv.org/abs/2411.06324
Autor:
Majumder, Al Saqib
Conventional economic and socio-behavioural models assume perfect symmetric access to information and rational behaviour among interacting agents in a social system. However, real-world events and observations appear to contradict such assumptions, l
Externí odkaz:
http://arxiv.org/abs/2411.06011
Advances in Autonomous Underwater Vehicles (AUVs) have evolved vastly in short period of time. While advancements in sonar and camera technology with deep learning aid the obstacle detection and path planning to a great extent, achieving the right ba
Externí odkaz:
http://arxiv.org/abs/2411.05516
We investigate how low-quality AI advisors, lacking quality disclosures, can help spread text-based lies while seeming to help people detect lies. Participants in our experiment discern truth from lies by evaluating transcripts from a game show that
Externí odkaz:
http://arxiv.org/abs/2410.23143