Learning Representations of Wordforms With Recurrent Networks: Comment on. - Jeffrey S. Bowers; Colin J. Davis (Cogn. Sci., 2009)

What is a grandmother cell? And how would you know if you found one? - Jeffrey S. Bowers (Connect. Sci., 2011)

The Effect of Test Format on Visual Recognition Memory Performance. - Nora Andermane; Jeffrey S. Bowers (CogSci, 2013)

Do voices survive lexical consolidation? - Nicolas Dumay; Jeffrey S. Bowers (CogSci, 2013)

When do PDP neural networks learn localist representations? - Ivan Vankov; Jeffrey S. Bowers (CogSci, 2013)

Using single unit recordings in PDP and localist models to better understand how knowledge is coded in the cortex. - Jeffrey S. Bowers (CogSci, 2017)

When and where do feed-forward neural networks learn localist representations? - Ella M. Gale; Nicolas Martin; Jeffrey S. Bowers (CoRR, 2018)

Translation Tolerance in Vision. - Ryan Blything; Ivan Vankov; Casimir J. H. Ludwig; Jeffrey S. Bowers (CogSci, 2019)

Selectivity metrics provide misleading estimates of the selectivity of single units in neural networks. - Ella Gale; Ryan Blything; Nicholas Martin; Jeffrey S. Bowers; Anh Nguyen 002 (CogSci, 2019)

The contrasting roles of shape in human vision and convolutional neural networks. - Gaurav Malhotra; Jeffrey S. Bowers (CogSci, 2019)

Out-of-the box neural networks can support combinatorial generalization. - Ivan Vankov; Jeffrey S. Bowers (CoRR, 2019)

Adding biological constraints to deep neural networks reduces their capacity to learn unstructured data. - Christian Tsvetkov; Gaurav Malhotra; Benjamin Evans; Jeffrey S. Bowers (CogSci, 2020)

Priorless Recurrent Networks Learn Curiously. - Jeff Mitchell 001; Jeffrey S. Bowers (COLING, 2020)

Harnessing the Symmetry of Convolutions for Systematic Generalisation. - Jeff Mitchell 001; Jeffrey S. Bowers (IJCNN, 2020)

Are there any 'object detectors' in the hidden layers of CNNs trained to identify objects or scenes? - Ella M. Gale; Nicholas Martin; Ryan Blything; Anh Nguyen 002; Jeffrey S. Bowers (CoRR, 2020)

Learning Translation Invariance in CNNs. - Valerio Biscione; Jeffrey S. Bowers (CoRR, 2020)

Can Deep Convolutional Neural Networks Learn Same-Different Relations? - Guillermo Puebla; Jeffrey S. Bowers (CogSci, 2021)

The role of Disentanglement in Generalisation. - Milton Llera Montero; Casimir J. H. Ludwig; Rui Ponte Costa; Gaurav Malhotra; Jeffrey S. Bowers (ICLR, 2021)

Generalisation in Neural Networks Does not Require Feature Overlap. - Jeff Mitchell 001; Jeffrey S. Bowers (CoRR, 2021)

Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be. - Valerio Biscione; Jeffrey S. Bowers (J. Mach. Learn. Res., 2021)

Lost in Latent Space: Examining failures of disentangled models at combinatorial generalisation. - Milton Llera Montero; Jeffrey S. Bowers; Rui Ponte Costa; Casimir J. H. Ludwig; Gaurav Malhotra (NeurIPS, 2022)

Do DNNs trained on Natural Images acquire Gestalt Properties? - Valerio Biscione; Jeffrey S. Bowers (CoRR, 2022)

Lost in Latent Space: Disentangled Models and the Challenge of Combinatorial Generalisation. - Milton Llera Montero; Jeffrey S. Bowers; Rui Ponte Costa; Casimir J. H. Ludwig; Gaurav Malhotra (CoRR, 2022)

Learning online visual invariances for novel objects via supervised and self-supervised training. - Valerio Biscione; Jeffrey S. Bowers (Neural Networks, 2022)

Biological convolutions improve DNN robustness to noise and generalisation. - Benjamin D. Evans; Gaurav Malhotra; Jeffrey S. Bowers (Neural Networks, 2022)

Feature blindness: A challenge for understanding and modelling visual object recognition. - Gaurav Malhotra; Marin Dujmovic; Jeffrey S. Bowers (PLoS Comput. Biol., 2022)

Convolutional Neural Networks Trained to Identify Words Provide a Good Account of Visual Form Priming Effects. - Dong Yin; Valerio Biscione; Jeffrey S. Bowers (CoRR, 2023)

The role of object-centric representations, guided attention, and external memory on generalizing visual relations. - Guillermo Puebla; Jeffrey S. Bowers (CoRR, 2023)

The role of capacity constraints in Convolutional Neural Networks for learning random versus natural data. - Christian Tsvetkov; Gaurav Malhotra; Benjamin D. Evans; Jeffrey S. Bowers (Neural Networks, 2023)

Successes and critical failures of neural networks in capturing human-like speech recognition. - Federico Adolfi; Jeffrey S. Bowers; David Poeppel (Neural Networks, 2023)

On the importance of severely testing deep learning models of cognition. - Jeffrey S. Bowers; Gaurav Malhotra; Federico Adolfi; Marin Dujmovic; Milton Llera Montero; Valerio Biscione; Guillermo Puebla; John E. Hummel; Rachel F. Heaton (Cogn. Syst. Res., 2023)

MindSet: Vision. A toolbox for testing DNNs on key psychological experiments. - Valerio Biscione; Dong Yin; Gaurav Malhotra; Marin Dujmovic; Milton Llera Montero; Guillermo Puebla; Federico Adolfi; Rachel F. Heaton; John E. Hummel; Benjamin D. Evans; Karim Habashy; Jeffrey S. Bowers (CoRR, 2024)

Adapting to time: why nature evolved a diverse set of neurons. - Karim Habashy; Benjamin D. Evans; Dan F. M. Goodman; Jeffrey S. Bowers (CoRR, 2024)

Successes and Limitations of Object-centric Models at Compositional Generalisation. - Milton L. Montero; Jeffrey S. Bowers; Gaurav Malhotra (CoRR, 2024)

Adapting to time: Why nature may have evolved a diverse set of neurons. - Karim Habashy; Benjamin D. Evans; Dan F. M. Goodman; Jeffrey S. Bowers (PLoS Comput. Biol., 2024)

Visual reasoning in object-centric deep neural networks: A comparative cognition approach. - Guillermo Puebla; Jeffrey S. Bowers (Neural Networks, 2025)