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20222026
most citedEfficient Causal Graph Discovery Using Large Language Models

6 citations · 10 across the 17 of their papers we have counts for

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8 papers · 1 filter

cs.LG2026

Delta-Crosscoder: Robust Crosscoder Model Diffing in Narrow Fine-Tuning Regimes

Aly Kassem, Thomas Jiralerspong, Negar Rostamzadeh +1

Model diffing methods aim to identify how fine-tuning changes a model's internal representations. Crosscoders approach this by learning shared dictionaries of interpretable latent…

cs.LG2025

Learning What Matters: Steering Diffusion via Spectrally Anisotropic Forward Noise

Luca Scimeca, Thomas Jiralerspong, Berton Earnshaw +2

Diffusion Probabilistic Models (DPMs) have achieved strong generative performance, yet their inductive biases remain largely implicit. In this work, we aim to build inductive biase…

cs.LG2025

Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control

Thomas Jiralerspong, Berton Earnshaw, Jason Hartford +2

Diffusion Probabilistic Models (DPMs) are powerful generative models that have achieved unparalleled success in a number of generative tasks. In this work, we aim to build inductiv…

cs.LG2024

General Causal Imputation via Synthetic Interventions

Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah +2

Given two sets of elements (such as cell types and drug compounds), researchers typically only have access to a limited subset of their interactions. The task of causal imputation…

cs.LG2024★ 6 cited

Efficient Causal Graph Discovery Using Large Language Models

Thomas Jiralerspong, Xiaoyin Chen, Yash More +2

We propose a novel framework that leverages LLMs for full causal graph discovery. While previous LLM-based methods have used a pairwise query approach, this requires a quadratic nu…

cs.LG2023★ 1 cited

A Comparison of Classical and Deep Reinforcement Learning Methods for HVAC Control

Marshall Wang, John Willes, Thomas Jiralerspong +1

Reinforcement learning (RL) is a promising approach for optimizing HVAC control. RL offers a framework for improving system performance, reducing energy consumption, and enhancing…