10 citations · 14 across the 12 of their papers we have counts for
12 papers
Entropy Equivalence Testing
Clément L. Canonne, Yash Pote, Jonathan Scarlett +1
We introduce the problem of \emph{entropy equivalence testing} for probability distributions, a relaxation of the well-studied closeness testing problem, where the distribution tes…
Instance Dependent Testing of Samplers using Interval Conditioning
Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote +2
Sampling algorithms play a pivotal role in probabilistic AI. However, verifying if a sampler program indeed samples from the claimed distribution is a notoriously hard problem. Pro…
A Distribution Testing Approach to Clustering Distributions
Gunjan Kumar, Yash Pote, Jonathan Scarlett
We study the following distribution clustering problem: Given a hidden partition of distributions into two groups, such that the distributions within each group are the same, a…
Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach
Clément L. Canonne, Yash Pote, Uddalok Sarkar
A growing fraction of all code is sampled from Large Language Models (LLMs). We investigate the problem of attributing code generated by language models using hypothesis testing to…
Learning Probabilistic Temporal Logic Specifications for Stochastic Systems
Rajarshi Roy, Yash Pote, David Parker +1
There has been substantial progress in the inference of formal behavioural specifications from sample trajectories, for example, using Linear Temporal Logic (LTL). However, these t…
Testing Self-Reducible Samplers
Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote +2
Samplers are the backbone of the implementations of any randomised algorithm. Unfortunately, obtaining an efficient algorithm to test the correctness of samplers is very hard to fi…
Distance Estimation for High-Dimensional Discrete Distributions
Gunjan Kumar, Kuldeep S. Meel, Yash Pote
Given two distributions and over a high-dimensional domain , and a parameter , the goal of distance estimation is to determine t…
On Scalable Testing of Samplers
Yash Pote, Kuldeep S. Meel
In this paper we study the problem of testing of constrained samplers over high-dimensional distributions with guarantees. Samplers are increasingly used in a w…
Efficiently Enabling Block Semantics and Data Updates in DNA Storage
Puru Sharma, Cheng-Kai Lim, Dehui Lin +2
We propose a novel and flexible DNA-storage architecture, which divides the storage space into fixed-size units (blocks) that can be independently and efficiently accessed at rando…
Managing Reliability Skew in DNA Storage
Dehui Lin, Yasamin Tabatabaee, Yash Pote +1
DNA is emerging as an increasingly attractive medium for data storage due to a number of important and unique advantages it offers, most notably the unprecedented durability and de…
Testing Probabilistic Circuits
Yash Pote, Kuldeep S. Meel
Probabilistic circuits (PCs) are a powerful modeling framework for representing tractable probability distributions over combinatorial spaces. In machine learning and probabilistic…
Partition Function Estimation: A Quantitative Study
Durgesh Agrawal, Yash Pote, Kuldeep S Meel
Probabilistic graphical models have emerged as a powerful modeling tool for several real-world scenarios where one needs to reason under uncertainty. A graphical model's partition…