Perceptual processes that create objects from fragments. - Philip J. Kellman (IJCNN, 2003)

Interpolation processes in the visual perception of objects. - Philip J. Kellman (Neural Networks, 2003)

Enhancing air traffic displays via perceptual cues. - Evan M. Palmer; Timothy C. Clausner; Philip J. Kellman (ACM Trans. Appl. Percept., 2008)

Perceptual Learning Modules in Mathematics: Enhancing Students' Pattern Recognition, Structure Extraction, and Fluency. - Philip J. Kellman; Christine M. Massey; Ji Y. Son (Top. Cogn. Sci., 2010)

Improving Adaptive Learning Technology through the Use of Response Times. - Everett Mettler; Christine M. Massey; Philip J. Kellman (CogSci, 2011)

Basic Information Processing Effects from Perceptual Learning in Complex, Real-World Domains. - Khanh-Phuong Thai; Everett Mettler; Philip J. Kellman (CogSci, 2011)

Challenges in Understanding Visual Shape Perception and Representation: Bridging Subsymbolic and Symbolic Coding. - Philip J. Kellman; Patrick Garrigan; Gennady Erlikhman (Shape Perception in Human and Computer Vision, 2013)

The Psychophysics of Algebra Expertise: Mathematics Perceptual Learning Interventions Produce Durable Encoding Changes. - Carolyn Bufford; Everett Mettler; Emma H. Geller; Philip J. Kellman (CogSci, 2014)

Connecting learning, memory, and representation in math education. - Martha W. Alibali; Chuck Kalish; Timothy T. Rogers; Christine M. Massey; Philip J. Kellman; Vladimir M. Sloutsky; James L. McClelland; Kevin W. Mickey (CogSci, 2015)

Perceptual Learning in Mathematics Produces Durable Encoding Improvements. - Carolyn Bufford; Philip J. Kellman (CogSci, 2015)

Adaptive Perceptual Learning in Electrocardiography: The Synergy of Passive and Active Classification. - Khanh-Phuong Thai; Sally Krasne; Philip J. Kellman (CogSci, 2015)

Perceptual Learning with Adaptively-triggered Comparisons. - Khanh-Phuong Thai; Sally Krasne; Philip J. Kellman (CogSci, 2015)

Deep Convolutional Networks do not Perceive Illusory Contours. - Nicholas Baker; Gennady Erlikhman; Philip J. Kellman; Hongjing Lu (CogSci, 2018)

Perceptual Learning in Correlation Estimation: The Role of Learning Category Organization. - Lucy Cui; Christine M. Massey; Philip J. Kellman (CogSci, 2018)

Enhancing Adaptive Learning through Strategic Scheduling of Passive and Active Learning Modes. - Everett Mettler; Christine M. Massey; Timothy Burke; Patrick Garrigan; Philip J. Kellman (CogSci, 2018)

Deep convolutional networks do not classify based on global object shape. - Nicholas Baker; Hongjing Lu; Gennady Erlikhman; Philip J. Kellman (PLoS Comput. Biol., 2018)

The Synergy of Passive and Active Learning Modes in Adaptive Perceptual Learning. - Everett Mettler; Philip J. Kellman; Austin Phillips; Timothy Burke; Christine M. Massey; Patrick Garrigan (CogSci, 2019)

Adaptive vs. Fixed Spacing of Learning Items: Evidence from Studies of Learning and Transfer in Chemistry Education. - Everett Mettler; Amina K. El-Ashmawy; Christine M. Massey; Philip J. Kellman (CogSci, 2020)

Comparing Adaptive and Random Spacing Schedules during Learning to Mastery Criteria. - Everett Mettler; Christine M. Massey; Timothy Burke; Philip J. Kellman (CogSci, 2020)

Comparisons in Adaptive Perceptual Category Learning. - Victoria L. Jacoby; Christine M. Massey; Everett Mettler; Philip J. Kellman (CogSci, 2022)

Configural relations in humans and deep convolutional neural networks. - Nicholas Baker; Patrick Garrigan; Austin Phillips; Philip J. Kellman (Frontiers Artif. Intell., 2022)

Connecting Adaptive Perceptual Learning and Signal Detection Theory in Skin Cancer Screening. - Philip J. Kellman; Christine M. Massey; Sally Krasne; Everett Mettler (CogSci, 2023)

Advances in the Study of Visual and Multisensory Objects. - Aleksandra Mroczko-Wasowicz; Casey O'Callaghan; Jonathan Cohen 003; Brian J. Scholl; Philip J. Kellman (CogSci, 2023)

Shape from dots: a window into abstraction processes in visual perception. - Nicholas Baker; Philip J. Kellman (Frontiers Comput. Sci., 2024)

Hierarchical Abstraction Enables Human-Like 3D Object Recognition in Deep Learning Models. - Shuhao Fu; Philip J. Kellman; Hongjing Lu (CoRR, 2025)