49 citations · 52 across the 11 of their papers we have counts for
11 papers
Critical discrete Hardy inequalities in
Krzysztof Bogdan, Shubham Gupta, Kamil Kaleta +1
We establish ground-state representations and critical Hardy inequalities in the discrete setting. In particular, we construct critical Hardy weights for the discrete Dirichl…
Sharp asymptotics for higher-order Hardy constants on lattices
Shubham Gupta
We study the optimal constants in higher-order Hardy inequalities on the lattice . For each fixed , we prove that the optimal constant $\mathcal{…
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
Private Map-Secure Reduce: Infrastructure for Efficient AI Data Markets
Sameer Wagh, Kenneth Stibler, Shubham Gupta +8
The modern AI data economy centralizes power, limits innovation, and misallocates value by extracting data without control, privacy, or fair compensation. We introduce Private Map-…
Data-driven learning of feedback maps for explicit robust predictive control: an approximation theoretic view
Siddhartha Ganguly, Shubham Gupta, Debasish Chatterjee
We establish an algorithm to learn feedback maps from data for a class of robust model predictive control (MPC) problems. The algorithm accounts for the approximation errors due to…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
LAST SToP For Modeling Asynchronous Time Series
Shubham Gupta, Thibaut Durand, Graham Taylor +1
We present a novel prompt design for Large Language Models (LLMs) tailored to Asynchronous Time Series. Unlike regular time series, which assume values at evenly spaced time points…
Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion
Nikolaos Livathinos, Christoph Auer, Maksym Lysak +14
We introduce Docling, an easy-to-use, self-contained, MIT-licensed, open-source toolkit for document conversion, that can parse several types of popular document formats into a uni…
Discrete functional inequalities on lattice graphs
Shubham Gupta
In this thesis, we study problems at the interface of analysis and discrete mathematics. We discuss analogues of well known Hardy-type inequalities and Rearrangement inequalities o…
SO-NeRF: Active View Planning for NeRF using Surrogate Objectives
Keifer Lee, Shubham Gupta, Sunglyoung Kim +3
Despite the great success of Neural Radiance Fields (NeRF), its data-gathering process remains vague with only a general rule of thumb of sampling as densely as possible. The lack…
Interactive Visualization of Time-Varying Flow Fields Using Particle Tracing Neural Networks
Mengjiao Han, Jixian Li, Sudhanshu Sane +4
In this paper, we present a comprehensive evaluation to establish a robust and efficient framework for Lagrangian-based particle tracing using deep neural networks (DNNs). Han et a…