Zobrazeno 1 - 10
of 28 508
pro vyhledávání: '"Malhotra, P."'
Autor:
Paliwal, Bhawna, Saini, Deepak, Dhawan, Mudit, Asokan, Siddarth, Natarajan, Nagarajan, Aggarwal, Surbhi, Malhotra, Pankaj, Jiao, Jian, Varma, Manik
Ranking a set of items based on their relevance to a given query is a core problem in search and recommendation. Transformer-based ranking models are the state-of-the-art approaches for such tasks, but they score each query-item independently, ignori
Externí odkaz:
http://arxiv.org/abs/2409.09795
Classification tasks present challenges due to class imbalances and evolving data distributions. Addressing these issues requires a robust method to handle imbalances while effectively detecting out-of-distribution (OOD) samples not encountered durin
Externí odkaz:
http://arxiv.org/abs/2409.00980
Autor:
Thakuria, Niharika, Malhotra, Akul, Thirumala, Sandeep K., Elangovan, Reena, Raghunathan, Anand, Gupta, Sumeet K.
Ternary Deep Neural Networks (DNN) have shown a large potential for highly energy-constrained systems by virtue of their low power operation (due to ultra-low precision) with only a mild degradation in accuracy. To enable an energy-efficient hardware
Externí odkaz:
http://arxiv.org/abs/2408.13617
We generalise Phinney's 'practical theorem' to account for modified graviton dispersion relations motivated by certain cosmological scenarios. Focusing on specific examples, we show how such modifications can induce characteristic localised distortio
Externí odkaz:
http://arxiv.org/abs/2408.10122
This paper introduces a Scalable Hierarchical Aware Convolutional Neural Network (SHA-CNN) model architecture for Edge AI applications. The proposed hierarchical CNN model is meticulously crafted to strike a balance between computational efficiency a
Externí odkaz:
http://arxiv.org/abs/2407.21370
Autor:
Khostovan, Ali Ahmad, Malhotra, Sangeeta, Rhoads, James E., Sobral, David, Harish, Santosh, Tilvi, Vithal, Coughlin, Alicia, Rezaee, Saeed
We investigate the `intrinsic' H$\alpha$ EW distributions of $z \sim 0.4 - 2.2$ narrowband-selected H$\alpha$ samples from HiZELS and DAWN using a forward modeling approach. We find an EW - stellar mass anti-correlation with steepening slopes $-0.18\
Externí odkaz:
http://arxiv.org/abs/2408.00080
Strong emission from doubly ionized oxygen is a beacon for some of the most intensely star forming galaxies known. JWST enables the search for this beacon in the early universe with unprecedented sensitivity. In this work, we extend the study of fain
Externí odkaz:
http://arxiv.org/abs/2407.19023
Air pollution remains one of the most formidable environmental threats to human health globally, particularly in urban areas, contributing to nearly 7 million premature deaths annually. Megacities, defined as cities with populations exceeding 10 mill
Externí odkaz:
http://arxiv.org/abs/2407.11283
Autor:
Schwöbel, Pola, Franceschi, Luca, Zafar, Muhammad Bilal, Vasist, Keerthan, Malhotra, Aman, Shenhar, Tomer, Tailor, Pinal, Yilmaz, Pinar, Diamond, Michael, Donini, Michele
fmeval is an open source library to evaluate large language models (LLMs) in a range of tasks. It helps practitioners evaluate their model for task performance and along multiple responsible AI dimensions. This paper presents the library and exposes
Externí odkaz:
http://arxiv.org/abs/2407.12872
Autor:
Khalatyan, A., Anders, F., Chiappini, C., Queiroz, A. B. A., Nepal, S., Ponte, M. dal, Jordi, C., Guiglion, G., Valentini, M., Elipe, G. Torralba, Steinmetz, M., Pantaleoni-González, M., Malhotra, S., Jiménez-Arranz, Ó., Enke, H., Casamiquela, L., Ardèvol, J.
In this paper, we explore the feasibility of using machine learning regression as a method of extracting basic stellar parameters and line-of-sight extinctions from spectro-photometric data. We built a stable gradient-boosted random-forest regressor
Externí odkaz:
http://arxiv.org/abs/2407.06963