Jascha Achterberg

According to our database, Jascha Achterberg authored at least 13 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

The Principle of Maximum Heterogeneity Optimises Productivity in Distributed Production Systems Across Biology, Economics, and Computing.

Guillhem Artis, Danyal Akarca, Jascha Achterberg

CoRR, April, 2026

2025

Algorithm-hardware co-design of neuromorphic networks with dual memory pathways.

Pengfei Sun, Zhe Su, Jascha Achterberg, Giacomo Indiveri, Dan F. M. Goodman, Danyal Akarca

CoRR, December, 2025

Exploiting heterogeneous delays for efficient computation in low-bit neural networks.

Pengfei Sun, Jascha Achterberg, Zhe Su, Dan F. M. Goodman, Danyal Akarca

CoRR, October, 2025

Brain-Like Processing Pathways Form in Models With Heterogeneous Experts.

Jack Cook, Danyal Akarca, Rui Ponte Costa, Jascha Achterberg

CoRR, June, 2025

Getting aligned on representational alignment.

Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Christopher J. Cueva, Erin Grant, Iris I. A. Groen, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine L. Hermann, Kerem Oktar, Klaus Greff, Martin N. Hebart, Nathan Cloos, Nikolaus Kriegeskorte, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P. O'Connell, Thomas Unterthiner, Andrew Kyle Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L. Griffiths

Trans. Mach. Learn. Res., 2025

2024

Accelerated AI Inference via Dynamic Execution Methods.

Haim Barad, Jascha Achterberg, Tien Pei Chou, Jean Yu

CoRR, 2024

Dynamical similarity analysis uniquely captures how computations develop in RNNs.

Quentin Guilhot, Jascha Achterberg, Michal Wójcik, Rui Ponte Costa

CoRR, 2024

Spatial embedding promotes a specific form of modularity with low entropy and heterogeneous spectral dynamics.

Cornelia Sheeran, Andrew S. Ham, Duncan E. Astle, Jascha Achterberg, Danyal Akarca

CoRR, 2024

Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience.

Zhonghao He, Jascha Achterberg, Katie Collins, Kevin K. Nejad, Danyal Akarca, Yinzhu Yang, Wes Gurnee, Ilia Sucholutsky, Yuhan Tang, Rebeca Ianov, George Ogden, Chole Li, Kai Sandbrink, Stephen Casper, Anna Ivanova, Grace W. Lindsay

CoRR, 2024

2023

Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings.

Jascha Achterberg, Danyal Akarca, D. J. Strouse, John Duncan, Duncan E. Astle

Nat. Mac. Intell., December, 2023

Getting aligned on representational alignment.

Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Erin Grant, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine L. Hermann, Kerem Oktar, Klaus Greff, Martin N. Hebart, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P. O'Connell, Thomas Unterthiner, Andrew K. Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L. Griffiths

CoRR, 2023

Brain-inspired learning in artificial neural networks: a review.

Samuel Schmidgall, Jascha Achterberg, Thomas Miconi, Louis Kirsch, Rojin Ziaei, S. Pardis Hajiseyedrazi, Jason Eshraghian

CoRR, 2023

Building artificial neural circuits for domain-general cognition: a primer on brain-inspired systems-level architecture.

Jascha Achterberg, Danyal Akarca, Moataz Assem, Moritz P. Heimbach, Duncan E. Astle, John Duncan

CoRR, 2023