Task-Driven Convolutional Recurrent Models of the Visual System. - Aran Nayebi; Daniel Bear; Jonas Kubilius; Kohitij Kar; Surya Ganguli; David Sussillo; James J. DiCarlo; Daniel L. K. Yamins (NeurIPS, 2018)

Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. - Jonas Kubilius; Martin Schrimpf; Ha Hong; Najib J. Majaj; Rishi Rajalingham; Elias B. Issa; Kohitij Kar; Pouya Bashivan; Jonathan Prescott-Roy; Kailyn Schmidt; Aran Nayebi; Daniel Bear; et al. (NeurIPS, 2019)

Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition. - Aran Nayebi; Javier Sagastuy-Breña; Daniel M. Bear; Kohitij Kar; Jonas Kubilius; Surya Ganguli; David Sussillo; James J. DiCarlo; Daniel L. K. Yamins (Neural Comput., 2022)

Interpretability of artificial neural network models in artificial intelligence versus neuroscience. - Kohitij Kar; Simon Kornblith; Evelina Fedorenko (Nat. Mac. Intell., 2022)

Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness. - Joel Dapello; Kohitij Kar; Martin Schrimpf; Robert Baldwin Geary; Michael Ferguson; David Daniel Cox; James J. DiCarlo (ICLR, 2023)

RTify: Aligning Deep Neural Networks with Human Behavioral Decisions. - Yu-Ang Cheng; Ivan F. Rodriguez Rodriguez; Sixuan Chen; Kohitij Kar; Takeo Watanabe; Thomas Serre (NeurIPS, 2024)

RTify: Aligning Deep Neural Networks with Human Behavioral Decisions. - Yu-Ang Cheng; Ivan Felipe Rodríguez; Sixuan Chen; Kohitij Kar; Takeo Watanabe; Thomas Serre (CoRR, 2024)