Jeffrey S. Bowers
Orcid: 0000-0001-9558-5010
According to our database1,
Jeffrey S. Bowers
authored at least 34 papers
between 2009 and 2024.
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Bibliography
2024
CoRR, 2024
Visual Reasoning in Object-Centric Deep Neural Networks: A Comparative Cognition Approach.
CoRR, 2024
2023
Cogn. Syst. Res., December, 2023
Successes and critical failures of neural networks in capturing human-like speech recognition.
Neural Networks, May, 2023
The role of capacity constraints in Convolutional Neural Networks for learning random versus natural data.
Neural Networks, April, 2023
The role of object-centric representations, guided attention, and external memory on generalizing visual relations.
CoRR, 2023
Convolutional Neural Networks Trained to Identify Words Provide a Good Account of Visual Form Priming Effects.
CoRR, 2023
2022
Feature blindness: A challenge for understanding and modelling visual object recognition.
PLoS Comput. Biol., 2022
Neural Networks, 2022
Learning online visual invariances for novel objects via supervised and self-supervised training.
Neural Networks, 2022
Lost in Latent Space: Disentangled Models and the Challenge of Combinatorial Generalisation.
CoRR, 2022
Lost in Latent Space: Examining failures of disentangled models at combinatorial generalisation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
2021
Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be.
J. Mach. Learn. Res., 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021
2020
Are there any 'object detectors' in the hidden layers of CNNs trained to identify objects or scenes?
CoRR, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the 28th International Conference on Computational Linguistics, 2020
Adding biological constraints to deep neural networks reduces their capacity to learn unstructured data.
Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020
2019
Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019
Selectivity metrics provide misleading estimates of the selectivity of single units in neural networks.
Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019
Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019
2018
CoRR, 2018
2017
Using single unit recordings in PDP and localist models to better understand how knowledge is coded in the cortex.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017
2013
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013
2011
Connect. Sci., 2011
2009
Cogn. Sci., 2009