75 citations · 280 across the 41 of their papers we have counts for
41 papers
Differentiable Repairability & Mutations for Scalable Combinatorial Optimization
Yongliang Sun, Ismail Alkhouri, Cheng-Han Huang +3
Combinatorial optimization problems such as Maximum Independent Set (MIS) and Maximum Cut (MaxCut) arise across a wide range of applications, yet solving large-scale instances rema…
On the Dataless Training of Neural Networks
Alvaro Velasquez, Susmit Jha, Ismail R. Alkhouri
This paper surveys studies on the use of neural networks for optimization in the training-data-free setting. Specifically, we examine the dataless application of neural network arc…
Concept-based Analysis of Neural Networks via Vision-Language Models
Ravi Mangal, Nina Narodytska, Divya Gopinath +4
The analysis of vision-based deep neural networks (DNNs) is highly desirable but it is very challenging due to the difficulty of expressing formal specifications for vision tasks a…
Direct Amortized Likelihood Ratio Estimation
Adam D. Cobb, Brian Matejek, Daniel Elenius +2
We introduce a new amortized likelihood ratio estimator for likelihood-free simulation-based inference (SBI). Our estimator is simple to train and estimates the likelihood ratio us…
math-PVS: A Large Language Model Framework to Map Scientific Publications to PVS Theories
Hassen Saidi, Susmit Jha, Tuhin Sahai
As artificial intelligence (AI) gains greater adoption in a wide variety of applications, it has immense potential to contribute to mathematical discovery, by guiding conjecture ge…
Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving
Sumit Kumar Jha, Susmit Jha, Patrick Lincoln +4
Generative large language models (LLMs) with instruct training such as GPT-4 can follow human-provided instruction prompts and generate human-like responses to these prompts. Apart…