NeurIPS 2023 Workshop InfoCog Submissions

Learning Causally Emergent Representations
Christos Kaplanis, Pedro Mediano, Fernando Rosas
- Published: 27 Oct 2023, Last Modified: 22 Nov 2023
- InfoCog@NeurIPS2023 Spotlight
- Readers: Everyone
An Information-Theoretic Understanding of Maximum Manifold Capacity Representations
Rylan Schaeffer, Berivan Isik, Victor Lecomte, Mikail Khona, Yann LeCun, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo
- Published: 27 Oct 2023, Last Modified: 27 Nov 2023
- InfoCog@NeurIPS2023 Spotlight
- Readers: Everyone
Aberrant High-Order Dependencies in Schizophrenia Resting-State Functional MRI Networks
Qiang LI, Vince Calhoun, Adithya Ram Ballem, Shujian Yu, Jesus Malo, Armin Iraji
- Published: 27 Oct 2023, Last Modified: 22 Nov 2023
- InfoCog@NeurIPS2023 Poster
- Readers: Everyone
A Work in Progress: Tighter Bounds on the Information Bottleneck for Deep Learning
Nir Weingarten, Moshe Butman, Ran Gilad-Bachrach
- Published: 27 Oct 2023, Last Modified: 09 Nov 2023
- InfoCog@NeurIPS2023 Poster
- Readers: Everyone
Lossy Compression and the Granularity of Causal Representation
David Kinney, Tania Lombrozo
- Published: 27 Oct 2023, Last Modified: 27 Nov 2023
- InfoCog@NeurIPS2023 Oral
- Readers: Everyone
Optimum Self-Random Number Generation Rate and Its Application to the Rate-Distortion-Perception-Problem
Ryo Nomura
- Published: 27 Oct 2023, Last Modified: 14 Dec 2023
- InfoCog@NeurIPS2023 Poster
- Readers: Everyone