Zobrazeno 1 - 10
of 42 220
pro vyhledávání: '"GOPALAKRISHNAN, A."'
Autor:
Narayan, Kartik, Nair, Nithin Gopalakrishnan, Xu, Jennifer, Chellappa, Rama, Patel, Vishal M.
Pre-training on large-scale datasets and utilizing margin-based loss functions have been highly successful in training models for high-resolution face recognition. However, these models struggle with low-resolution face datasets, in which the faces l
Externí odkaz:
http://arxiv.org/abs/2412.07771
We consider the relaxation of finite-wavevector density waves in a facilitated classical lattice gas. Linear hydrodynamics predicts that such perturbations should relax exponentially, but nonlinear effects were predicted to cause subexponential relax
Externí odkaz:
http://arxiv.org/abs/2412.05222
As machine learning gets deployed more and more widely, and model sizes continue to grow, improving computational efficiency during model inference has become a key challenge. In many commonly used model architectures, including Transformers, a signi
Externí odkaz:
http://arxiv.org/abs/2412.00408
We present DiffVox, a self-supervised framework for Cone-Beam Computed Tomography (CBCT) reconstruction by directly optimizing a voxelgrid representation using physics-based differentiable X-ray rendering. Further, we investigate how the different im
Externí odkaz:
http://arxiv.org/abs/2411.19224
Deep learning-based models for All-In-One Image Restoration (AIOR) have achieved significant advancements in recent years. However, their practical applicability is limited by poor generalization to samples outside the training distribution. This lim
Externí odkaz:
http://arxiv.org/abs/2411.17687
Autor:
Qu, Yi-Fan, Stefanini, Martino, Shi, Tao, Esslinger, Tilman, Gopalakrishnan, Sarang, Marino, Jamir, Demler, Eugene
Recent experiments with quantum simulators using ultracold atoms and superconducting qubits have demonstrated the potential of controlled dissipation as a versatile tool for realizing correlated many-body states. However, determining the dynamics of
Externí odkaz:
http://arxiv.org/abs/2411.13638
We investigate the thermodynamic limits on scaling fault-tolerant quantum computers due to heating from quantum error correction (QEC). Quantum computers require error correction, which accounts for 99.9% of the qubit demand and generates heat throug
Externí odkaz:
http://arxiv.org/abs/2411.12805
We consider one dimensional many-particle systems that exhibit kinematically protected single-particle excitations over their ground states. We show that momentum and time-resolved 4-point functions of operators that create such excitations diverge l
Externí odkaz:
http://arxiv.org/abs/2411.06167
Autor:
Sengupta, Ayan, Seth, Vaibhav, Pathak, Arinjay, Raman, Natraj, Gopalakrishnan, Sriram, Chakraborty, Tanmoy
Large Language Models (LLMs) are highly resource-intensive to fine-tune due to their enormous size. While low-rank adaptation is a prominent parameter-efficient fine-tuning approach, it suffers from sensitivity to hyperparameter choices, leading to i
Externí odkaz:
http://arxiv.org/abs/2411.04358
We consider measurement-induced phase transitions in monitored quantum circuits with a measurement rate that fluctuates in time. The spatially correlated fluctuations in the measurement rate disrupt the volume-law phase for low measurement rates; at
Externí odkaz:
http://arxiv.org/abs/2411.03442