SUSTAIN: A Model of Human Category Learning. - Bradley C. Love; Douglas L. Medin (AAAI/IAAI, 1998)

Utilizing lime: Asynchronous Binding. - Bradley C. Love (NIPS, 1998)

Feature Centrality and Conceptual Coherence. - Steven A. Sloman; Bradley C. Love; Woo-Kyoung Ahn (Cogn. Sci., 1998)

Modeling Classification and Inference Learning. - Bradley C. Love; Arthur B. Markman; Takashi Yamauchi (AAAI/IAAI, 2000)

Modeling Unsupervised Learning with SUSTAIN. - Todd M. Gureckis; Bradley C. Love (FLAIRS, 2002)

Similarity and Categorization: A Review. - Bradley C. Love (AI Mag., 2002)

CAB: Connectionist Analogy Builder. - Levi B. Larkey; Bradley C. Love (Cogn. Sci., 2003)

Human Unsupervised and Supervised Learning as a Quantitative Distinction. - Todd M. Gureckis; Bradley C. Love (Int. J. Pattern Recognit. Artif. Intell., 2003)

Towards a unified account of supervised and unsupervised category learning. - Todd M. Gureckis; Bradley C. Love (J. Exp. Theor. Artif. Intell., 2003)

Dimension-Wide vs. Exemplar-Specific Attention in Category Learning and Recognition. - Yasuaki Sakamoto; Toshihiko Matsuka; Bradley C. Love (ICCM, 2004)

From Pigeons to Humans: Grounding Relational Learning in Concrete Examples. - Marc T. Tomlinson; Bradley C. Love (AAAI, 2006)

Learning to predict information needs: context-aware display as a cognitive aid and an assessment tool. - Bradley C. Love; Matt Jones 002; Marc T. Tomlinson; Michael Howe (CHI, 2009)

Seeing the World through an Expert's Eyes: Context-Aware Display as a Training Companion. - Marc T. Tomlinson; Michael Howe; Bradley C. Love (HCI (16), 2009)

Patient education on mobile devices: an e-health intervention for low health literate audiences. - Michael Mackert; Bradley C. Love; Pamela Whitten (J. Inf. Sci., 2009)

Direct Associations or Internal Transformations? Exploring the Mechanisms Underlying Sequential Learning Behavior. - Todd M. Gureckis; Bradley C. Love (Cogn. Sci., 2010)

Determinants of learning difficulty and boundary uncertainty in unidimensional category learning. - Gyslain Giguère; Bradley C. Love (CogSci, 2011)

Becoming a Gamer: Cognitive Effects of Real-Time Strategy Gaming. - Brian D. Glass; Marc T. Tomlinson; W. Todd Maddox; Bradley C. Love (CogSci, 2011)

Moving Beyond Where and What to How: Using Models and fMRI to Understand Brain-Behavior Relations. - Bradley C. Love; John P. Spencer; Nathaniel D. Daw; John P. O'Doherty (CogSci, 2011)

Computational, Neuroscientific, and Lifespan Perspectives on the Exploration-Exploitation Dilemma. - A. Ross Otto; W. Bradley Knox; Bradley C. Love; Samuel Gershman; Yael Niv; Darrell A. Worthy; W. Todd Maddox; Jared M. Hotaling; Jerome R. Busemeyer; Richard M. Shiffrin (CogSci, 2011)

Structural Priming as Structure-Mapping: Children Use Analogies From Previous Utterances to Guide Sentence Production. - Micah B. Goldwater; Marc T. Tomlinson; Catharine H. Echols; Bradley C. Love (Cogn. Sci., 2011)

Thirty years of Marr's Vision: Levels of Analysis in Cognitive Science. - Chris Eliasmith; Thomas L. Griffiths 001; Valerie Gray Hardcastle; Bradley C. Love; William Bechtel; Richard P. Cooper 002; David Peebles (CogSci, 2012)

Exploring Psychosocial Support Online: A Content Analysis of Messages in an Adolescent and Young Adult Cancer Community. - Bradley C. Love; Brittani Crook; Charee M. Thompson; Sarah Zaitchik; Jessica Knapp; Leah LeFebvre; Barbara Jones; Erin Donovan-Kicken; Emily Eargle; Ruth Rechis (Cyberpsychology Behav. Soc. Netw., 2012)

How Humans Teach Agents - A New Experimental Perspective. - W. Bradley Knox; Brian D. Glass; Bradley C. Love; W. Todd Maddox; Peter Stone 001 (Int. J. Soc. Robotics, 2012)

Are forgetting processes crucial to category learning? - Lukasz Kopec; Bradley C. Love (CogSci, 2013)

When is it rational to rely on heuristics? - Paula Parpart; Matt Jones 002; Bradley C. Love (CogSci, 2013)

Experiments in dynamic group action and decision making: How crowds of people can walk a tightrope together and survive a zombie attack. - Daniel C. Richardson; Peter S. Riefer; Bradley C. Love; Beau Lotto; Richard C. Clarke; Rick Dale; John Rogers; James Ireland (CogSci, 2013)

Moot Point Process Models. - Bradley C. Love; Jana Jarecki; Jerome R. Busemeyer; Niels A. Taatgen; Thomas L. Griffiths 001; Mirjam Jenny (CogSci, 2014)

Heuristics as a special case of Bayesian Inference. - Paula Parpart; Matt Jones 002; Bradley C. Love (CogSci, 2014)

Choice exploration and exploitation in purchase decisions: a longitudinal study of customers' exploration and exploitation of supermarket products. - Peter S. Riefer; Bradley C. Love (CogSci, 2014)

Optimal Teaching for Limited-Capacity Human Learners. - Kaustubh R. Patil; Xiaojin Zhu 001; Lukasz Kopec; Bradley C. Love (NIPS, 2014)

"You may have a cancer-causing virus and not even know it" Fear appeals in online news. - Bradley C. Love; Michael Mackert (First Monday, 2014)

Generative and Discriminative Models in Cognitive Science. - Bradley C. Love; Michael Ramscar; Thomas L. Griffiths 001; Matt Jones 002 (CogSci, 2015)

Active learning as a means to distinguish among prominent decision strategies. - Paula Parpart; Eric Schulz; Maarten Speekenbrink; Bradley C. Love (CogSci, 2015)

Unfazed by Both the Bull and Bear: Strategic Exploration in Dynamic Environments. - Peter S. Riefer; Bradley C. Love (Games, 2015)

The Algorithmic Level Is the Bridge Between Computation and Brain. - Bradley C. Love (Top. Cogn. Sci., 2015)

Deep Networks as Models of Human and Animal Categorization. - Bradley C. Love; Olivia Guest; Piotr Slomka; Victor Navarro; Edward Wasserman (CogSci, 2017)

Medial prefrontal cortex compresses concept representations through learning. - Michael L. Mack; Alison R. Preston; Bradley C. Love (PRNI, 2017)

Anterior Temporal Lobe Tracks the Formation of Prejudice. - Hugo J. Spiers; Bradley C. Love; Mike E. Le Pelley; Charlotte E. Gibb; Robin A. Murphy (J. Cogn. Neurosci., 2017)

Conceptual Organization is Revealed by Consumer Activity Patterns. - Adam N. Hornsby; Thomas Evans; Peter S. Riefer; Rosie Prior; Bradley C. Love (CoRR, 2018)

Estimating the functional dimensionality of neural representations. - Christiane Ahlheim; Bradley C. Love (NeuroImage, 2018)

Gerrymandering and computational redistricting. - Olivia Guest; Frank J. Kanayet; Bradley C. Love (J. Comput. Soc. Sci., 2019)

The Costs and Benefits of Goal-Directed Attention in Deep Convolutional Neural Networks. - Xiaoliang Luo; Brett D. Roads; Bradley C. Love (CoRR, 2020)

The perceptual boost of visual attention is task-dependent in naturalistic settings. - Freddie Bickford Smith; Xiaoliang Luo; Brett D. Roads; Bradley C. Love (CoRR, 2020)

Robust priors for regularized regression. - Sebastian Bobadilla-Suarez; Matt Jones 002; Bradley C. Love (CoRR, 2020)

Learning as the unsupervised alignment of conceptual systems. - Brett D. Roads; Bradley C. Love (Nat. Mach. Intell., 2020)

Enriching ImageNet With Human Similarity Judgments and Psychological Embeddings. - Brett D. Roads; Bradley C. Love (CVPR, 2021)

Understanding top-down attention using task-oriented ablation design. - Freddie Bickford Smith; Brett D. Roads; Xiaoliang Luo; Bradley C. Love (CoRR, 2021)

Exploring Alignment of Representations with Human Perception. - Vedant Nanda; Ayan Majumdar; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Bradley C. Love; Adrian Weller (CoRR, 2021)

Confound-leakage: Confound Removal in Machine Learning Leads to Leakage. - Sami Hamdan; Bradley C. Love; Georg G. von Polier; Susanne Weis; Holger Schwender; Simon B. Eickhoff; Kaustubh R. Patil (CoRR, 2022)

Web-based Elicitation of Human Perception on mixup Data. - Katherine M. Collins; Umang Bhatt; Weiyang Liu; Vihari Piratla; Bradley C. Love; Adrian Weller (CoRR, 2022)

Abstract Neural Representations of Category Membership beyond Information Coding Stimulus or Response. - Robert M. Mok; Bradley C. Love (J. Cogn. Neurosci., 2022)

Do Invariances in Deep Neural Networks Align with Human Perception? - Vedant Nanda; Ayan Majumdar; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Bradley C. Love; Adrian Weller (AAAI, 2023)

Human-in-the-Loop Mixup. - Katherine M. Collins; Umang Bhatt; Weiyang Liu; Vihari Piratla; Ilia Sucholutsky; Bradley C. Love; Adrian Weller (UAI, 2023)

Getting aligned on representational alignment. - Ilia Sucholutsky; Lukas Muttenthaler; Adrian Weller; Andi Peng; Andreea Bobu; Been Kim; Bradley C. Love; Erin Grant; Jascha Achterberg; Joshua B. Tenenbaum; Katherine M. Collins; Katherine L. Hermann; et al. (CoRR, 2023)

On Leakage in Machine Learning Pipelines. - Leonard Sasse; Eliana Nicolaisen-Sobesky; Juergen Dukart; Simon B. Eickhoff; Michael Götz; Sami Hamdan; Vera Komeyer; Abhijit Kulkarni; Juha Lahnakoski; Bradley C. Love; Federico Raimondo; Kaustubh R. Patil (CoRR, 2023)

A too-good-to-be-true prior to reduce shortcut reliance. - Nikolay Dagaev; Brett D. Roads; Xiaoliang Luo; Daniel N. Barry; Kaustubh R. Patil; Bradley C. Love (Pattern Recognit. Lett., 2023)

Large language models surpass human experts in predicting neuroscience results. - Xiaoliang Luo; Akilles Rechardt; Guangzhi Sun; Kevin K. Nejad; Felipe Yáñez; Bati Yilmaz; Kangjoo Lee; Alexandra O. Cohen; Valentina Borghesani; Anton Pashkov; Daniele Marinazzo; Jonathan Nicholas; et al. (CoRR, 2024)

Matching domain experts by training from scratch on domain knowledge. - Xiaoliang Luo; Guangzhi Sun; Bradley C. Love (CoRR, 2024)

Representational Alignment Supports Effective Machine Teaching. - Ilia Sucholutsky; Katherine M. Collins; Maya Malaviya; Nori Jacoby; Weiyang Liu; Theodore R. Sumers; Michalis Korakakis; Umang Bhatt; Mark K. Ho; Joshua B. Tenenbaum; Bradley C. Love; Zachary A. Pardos; et al. (CoRR, 2024)

Confidence-weighted integration of human and machine judgments for superior decision-making. - Felipe Yáñez; Xiaoliang Luo; Omar Valerio Minero; Bradley C. Love (CoRR, 2024)

Beyond Human-Like Processing: Large Language Models Perform Equivalently on Forward and Backward Scientific Text. - Xiaoliang Luo; Michael Ramscar; Bradley C. Love (CoRR, 2024)

Probability Consistency in Large Language Models: Theoretical Foundations Meet Empirical Discrepancies. - Xiaoliang Luo; Xinyi Xu; Michael Ramscar; Bradley C. Love (CoRR, 2025)

Overview of leakage scenarios in supervised machine learning. - Leonard Sasse; Eliana Nicolaisen-Sobesky; Juergen Dukart; Simon B. Eickhoff; Michael Götz; Sami Hamdan; Vera Komeyer; Abhijit Kulkarni; Juha Lahnakoski; Bradley C. Love; Federico Raimondo; Kaustubh R. Patil (J. Big Data, 2025)