On the Information Bottleneck Theory of Deep Learning. - Andrew M. Saxe; Yamini Bansal; Joel Dapello; Madhu Advani; Artemy Kolchinsky; Brendan D. Tracey; David D. Cox (ICLR (Poster), 2018)

Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations. - Joel Dapello; Tiago Marques; Martin Schrimpf; Franziska Geiger; David D. Cox; James J. DiCarlo (NeurIPS, 2020)

Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception. - Joel Dapello; Jenelle Feather; Hang Le 002; Tiago Marques; David D. Cox; Josh H. McDermott; James J. DiCarlo; SueYeon Chung (NeurIPS, 2021)

Combining Different V1 Brain Model Variants to Improve Robustness to Image Corruptions in CNNs. - Avinash Baidya; Joel Dapello; James J. DiCarlo; Tiago Marques (CoRR, 2021)

Adversarially trained neural representations are already as robust as biological neural representations. - Chong Guo; Michael J. Lee; Guillaume Leclerc; Joel Dapello; Yug Rao; Aleksander Madry; James J. DiCarlo (ICML, 2022)

Adversarially trained neural representations may already be as robust as corresponding biological neural representations. - Chong Guo; Michael J. Lee; Guillaume Leclerc; Joel Dapello; Yug Rao; Aleksander Madry; James J. DiCarlo (CoRR, 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)

ProtoGraph: A Non-Expert Toolkit for Creating Animated Graphs. - Malchiel Rodrigues; Joel Dapello; Priyan Vaithilingam; Carolina Nobre; Johanna Beyer (IEEE VIS (Short Papers), 2023)

Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds. - Michael Kuoch; Chi-Ning Chou; Nikhil Parthasarathy; Joel Dapello; James J. DiCarlo; Haim Sompolinsky; SueYeon Chung (CPAL, 2024)