activity
20172024
most citedVisualizing probabilistic models: Intensive Principal Component Analysis

37 citations · 135 across the 10 of their papers we have counts for

collaborators

11 papers

cond-mat.dis-nn2024★ 4 cited

Inverse Melting of Polar Order in Chemically Substituted BaTiO3

Yang Zhang, Suk Hyun Sung, Colin B. Clement +2

In many condensed matter systems, long range order emerges at low temperatures as thermal fluctuations subside. In the presence of competing interactions or quenched disorder, howe…

cs.IR2021★ 1 cited

Distilling Transformers for Neural Cross-Domain Search

Colin B. Clement, Chen Wu, Dawn Drain +1

Pre-trained transformers have recently clinched top spots in the gamut of natural language tasks and pioneered solutions to software engineering tasks. Even information retrieval h…

cs.SE2021★ 14 cited

DeepDebug: Fixing Python Bugs Using Stack Traces, Backtranslation, and Code Skeletons

Dawn Drain, Colin B. Clement, Guillermo Serrato +1

The joint task of bug localization and program repair is an integral part of the software development process. In this work we present DeepDebug, an approach to automated debugging…

cs.LG2020★ 1 cited

PyMT5: multi-mode translation of natural language and Python code with transformers

Colin B. Clement, Dawn Drain, Jonathan Timcheck +2

Simultaneously modeling source code and natural language has many exciting applications in automated software development and understanding. Pursuant to achieving such technology,…

cond-mat.stat-mech2019★ 12 cited

Visualizing probabilistic models in Minkowski space with intensive symmetrized Kullback-Leibler embedding

Han Kheng Teoh, Katherine N. Quinn, Jaron Kent-Dobias +3

We show that the predicted probability distributions for any -parameter statistical model taking the form of an exponential family can be explicitly and analytically embedded is…

physics.data-an2019★ 4 cited

Reconstruction of Current Densities from Magnetic Images by Bayesian Inference

Colin B. Clement, James P. Sethna, Katja C. Nowack

Electronic transport is at the heart of many phenomena in condensed matter physics and material science. Magnetic imaging is a non-invasive tool for detecting electric current in m…

cs.IR2019★ 23 cited

On the Use of ArXiv as a Dataset

Colin B. Clement, Matthew Bierbaum, Kevin P. O'Keeffe +1

The arXiv has collected 1.5 million pre-print articles over 28 years, hosting literature from scientific fields including Physics, Mathematics, and Computer Science. Each pre-print…

cond-mat.stat-mech2018★ 37 cited

Visualizing probabilistic models: Intensive Principal Component Analysis

Katherine N. Quinn, Colin B. Clement, Francesco De Bernardis +2

Unsupervised learning makes manifest the underlying structure of data without curated training and specific problem definitions. However, the inference of relationships between dat…

physics.data-an2018★ 4 cited

Image registration and super resolution from first principles

Colin B. Clement, Matthew Bierbaum, James P. Sethna

Image registration is the inference of transformations relating noisy and distorted images. It is fundamental in computer vision, experimental physics, and medical imaging. Many al…

eess.SP2017

Image registration of low signal-to-noise cryo-STEM data

Benjamin H. Savitzky, Ismail El Baggari, Colin Clement +9

Combining multiple fast image acquisitions to mitigate scan noise and drift artifacts has proven essential for picometer precision, quantitative analysis of atomic resolution scann…

cond-mat.stat-mech2017★ 35 cited

Normal form for renormalization groups

Archishman Raju, Colin B. Clement, Lorien X. Hayden +4

The results of the renormalization group are commonly advertised as the existence of power law singularities near critical points. The classic predictions are often violated and lo…