Max Tegmark

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 75

Top Topics

Formal Language

Artificial Intelligence

Top Venues

Publications

Stephen Casper, Carson Ezell, Charlotte Siegmann, Noam Kolt, Taylor Lynn Curtis, Benjamin Bucknall, Andreas A. Haupt, Kevin Wei, Jérémy Scheurer, Marius Hobbhahn, Lee Sharkey, Satyapriya Krishna, Marvin Von Hagen, Silas Alberti, Alan Chan, Qinyi Sun, Michael Gerovitch, David Bau, Max Tegmark, David Krueger, Dylan Hadfield-Menell
Black-Box Access is Insufficient for Rigorous AI Audits. FAccT (2024)
Stephen Casper, Carson Ezell, Charlotte Siegmann, Noam Kolt, Taylor Lynn Curtis, Benjamin Bucknall, Andreas Alexander Haupt, Kevin Wei, Jérémy Scheurer, Marius Hobbhahn, Lee Sharkey, Satyapriya Krishna, Marvin Von Hagen, Silas Alberti, Alan Chan, Qinyi Sun, Michael Gerovitch, David Bau, Max Tegmark, David Krueger, Dylan Hadfield-Menell
Black-Box Access is Insufficient for Rigorous AI Audits. CoRR (2024)
Eric J. Michaud, Isaac Liao, Vedang Lad, Ziming Liu, Anish Mudide, Chloe Loughridge, Zifan Carl Guo, Tara Rezaei Kheirkhah, Mateja Vukelic, Max Tegmark
Opening the AI black box: program synthesis via mechanistic interpretability. CoRR (2024)
Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson, Marin Soljacic, Thomas Y. Hou, Max Tegmark
KAN: Kolmogorov-Arnold Networks. CoRR (2024)
David D. Baek, Ziming Liu, Max Tegmark
GenEFT: Understanding Statics and Dynamics of Model Generalization via Effective Theory. CoRR (2024)
Xiaoman Delores Ding, Zifan Carl Guo, Eric J. Michaud, Ziming Liu, Max Tegmark
Survival of the Fittest Representation: A Case Study with Modular Addition. CoRR (2024)
Chloe Loughridge, Qinyi Sun, Seth Ahrenbach, Federico Cassano, Chuyue Sun, Ying Sheng, Anish Mudide, Md Rakib Hossain Misu, Nada Amin, Max Tegmark
DafnyBench: A Benchmark for Formal Software Verification. CoRR (2024)
Subhash Kantamneni, Ziming Liu, Max Tegmark
How Do Transformers "Do" Physics? Investigating the Simple Harmonic Oscillator. CoRR (2024)
Jinyeop Song, Ziming Liu, Max Tegmark, Jeff Gore
A Resource Model For Neural Scaling Law. CoRR (2024)
David Dalrymple, Joar Skalse, Yoshua Bengio, Stuart Russell, Max Tegmark, Sanjit Seshia, Steve Omohundro, Christian Szegedy, Ben Goldhaber, Nora Ammann, Alessandro Abate, Joe Halpern, Clark W. Barrett, Ding Zhao, Tan Zhi-Xuan, Jeannette Wing, Joshua B. Tenenbaum
Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. CoRR (2024)
Wes Gurnee, Max Tegmark
Language Models Represent Space and Time. ICLR (2024)
Subhash Kantamneni, Ziming Liu, Max Tegmark
OptPDE: Discovering Novel Integrable Systems via AI-Human Collaboration. CoRR (2024)
Joshua Engels, Isaac Liao, Eric J. Michaud, Wes Gurnee, Max Tegmark
Not All Language Model Features Are Linear. CoRR (2024)
Ziming Liu, Eric Gan, Max Tegmark
Seeing Is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability. Entropy 26 (1) (2024)
Vedang Lad, Wes Gurnee, Max Tegmark
The Remarkable Robustness of LLMs: Stages of Inference? CoRR (2024)
Eric J. Michaud, Ziming Liu, Uzay Girit, Max Tegmark
The Quantization Model of Neural Scaling. NeurIPS (2023)
Isaac Liao, Ziming Liu, Max Tegmark
Generating Interpretable Networks using Hypernetworks. CoRR (2023)
Ziming Liu, Eric Gan, Max Tegmark
Seeing is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability. CoRR (2023)
Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. CoRR (2023)
Ziming Liu, Patrick Obin Sturm, Saketh Bharadwaj, Sam Silva, Max Tegmark
Discovering New Interpretable Conservation Laws as Sparse Invariants. CoRR (2023)
Wes Gurnee, Max Tegmark
Language Models Represent Space and Time. CoRR (2023)
Ziming Liu, Max Tegmark
A Neural Scaling Law from Lottery Ticket Ensembling. CoRR (2023)
Samuel Marks, Max Tegmark
The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets. CoRR (2023)
Ziming Liu, Ziqian Zhong, Max Tegmark
Grokking as Compression: A Nonlinear Complexity Perspective. CoRR (2023)
Peter S. Park, Max Tegmark
Divide-and-Conquer Dynamics in AI-Driven Disempowerment. CoRR (2023)
Max Tegmark, Steve Omohundro
Provably safe systems: the only path to controllable AGI. CoRR (2023)
Ziming Liu, Di Luo, Yilun Xu, Tommi S. Jaakkola, Max Tegmark
GenPhys: From Physical Processes to Generative Models. CoRR (2023)
Ziqian Zhong, Ziming Liu, Max Tegmark, Jacob Andreas
The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks. CoRR (2023)
Eric J. Michaud, Ziming Liu, Max Tegmark
Precision Machine Learning. Entropy 25 (1) (2023)
Ziming Liu, Eric J. Michaud, Max Tegmark
Omnigrok: Grokking Beyond Algorithmic Data. ICLR (2023)
Ziqian Zhong, Ziming Liu, Max Tegmark, Jacob Andreas
The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks. NeurIPS (2023)
Eric J. Michaud, Ziming Liu, Uzay Girit, Max Tegmark
The Quantization Model of Neural Scaling. CoRR (2023)
Ziming Liu, Mikail Khona, Ila R. Fiete, Max Tegmark
Growing Brains: Co-emergence of Anatomical and Functional Modularity in Recurrent Neural Networks. CoRR (2023)
Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. ICML (2023)
Alexander Zlokapa, Andrew K. Tan, John M. Martyn, Max Tegmark, Isaac L. Chuang
Biological error correction codes generate fault-tolerant neural networks. CoRR (2022)
Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola
Poisson Flow Generative Models. NeurIPS (2022)
Andrew K. Tan, Max Tegmark, Isaac L. Chuang
Pareto-optimal clustering with the primal deterministic information bottleneck. CoRR (2022)
Michael Skuhersky, Tailin Wu, Eviatar Yemini, Amin Nejatbakhsh, Edward S. Boyden, Max Tegmark
Toward a more accurate 3D atlas of C. elegans neurons. BMC Bioinform. 23 (1) (2022)
Eric J. Michaud, Ziming Liu, Max Tegmark
Precision Machine Learning. CoRR (2022)
Ziming Liu, Ouail Kitouni, Niklas Nolte, Eric J. Michaud, Max Tegmark, Mike Williams
Towards Understanding Grokking: An Effective Theory of Representation Learning. NeurIPS (2022)
Ziming Liu, Varun Madhavan, Max Tegmark
AI Poincaré 2.0: Machine Learning Conservation Laws from Differential Equations. CoRR (2022)
Ziming Liu, Eric J. Michaud, Max Tegmark
Omnigrok: Grokking Beyond Algorithmic Data. CoRR (2022)
Ziming Liu, Ouail Kitouni, Niklas Nolte, Eric J. Michaud, Max Tegmark, Mike Williams
Towards Understanding Grokking: An Effective Theory of Representation Learning. CoRR (2022)
Andrew K. Tan, Max Tegmark, Isaac L. Chuang
Pareto-Optimal Clustering with the Primal Deterministic Information Bottleneck. Entropy 24 (6) (2022)
Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola
Poisson Flow Generative Models. CoRR (2022)
Ziming Liu, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu
Machine-Learning Non-Conservative Dynamics for New-Physics Detection. CoRR (2021)
Samantha D'Alonzo, Max Tegmark
Machine-Learning media bias. CoRR (2021)
Ziming Liu, Max Tegmark
Machine-learning hidden symmetries. CoRR (2021)
Ziming Liu, Yunyue Chen, Yuanqi Du, Max Tegmark
Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning. CoRR (2021)
Silviu-Marian Udrescu, Andrew K. Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity. NeurIPS (2020)
Ziming Liu, Max Tegmark
AI Poincaré: Machine Learning Conservation Laws from Trajectories. CoRR (2020)
Silviu-Marian Udrescu, Max Tegmark
Symbolic Pregression: Discovering Physical Laws from Raw Distorted Video. CoRR (2020)
Max Tegmark, Tailin Wu
Pareto-Optimal Data Compression for Binary Classification Tasks. Entropy 22 (1) (2020)
Silviu-Marian Udrescu, Andrew K. Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity. CoRR (2020)
Tailin Wu, Ian S. Fischer, Isaac L. Chuang, Max Tegmark
Learnability for the Information Bottleneck. Entropy 21 (10) (2019)
Tailin Wu, Ian S. Fischer, Isaac L. Chuang, Max Tegmark
Learnability for the Information Bottleneck. UAI (2019)
Max Tegmark, Tailin Wu
Pareto-optimal data compression for binary classification tasks. CoRR (2019)
Ricardo Vinuesa, Hossein Azizpour, Iolanda Leite, Madeline Balaam, Virginia Dignum, Sami Domisch, Anna Felländer, Simone Langhans, Max Tegmark, Francesco Fuso Nerini
The role of artificial intelligence in achieving the Sustainable Development Goals. CoRR (2019)
Tailin Wu, Ian S. Fischer, Isaac L. Chuang, Max Tegmark
Learnability for the Information Bottleneck. CoRR (2019)
Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
Gated Orthogonal Recurrent Units: On Learning to Forget. Neural Comput. 31 (4) (2019)
Silviu-Marian Udrescu, Max Tegmark
AI Feynman: a Physics-Inspired Method for Symbolic Regression. CoRR (2019)
Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
Gated Orthogonal Recurrent Units: On Learning to Forget. AAAI Workshops (2018)
Tailin Wu, Max Tegmark
Toward an AI Physicist for Unsupervised Learning. CoRR (2018)
David Rolnick, Max Tegmark
The power of deeper networks for expressing natural functions. ICLR (Poster) (2018)
Tailin Wu, John Peurifoy, Isaac L. Chuang, Max Tegmark
Meta-learning autoencoders for few-shot prediction. CoRR (2018)
Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Yann LeCun, Max Tegmark, Marin Soljacic
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs. ICML (2017)
Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
Gated Orthogonal Recurrent Units: On Learning to Forget. CoRR (2017)
David Rolnick, Max Tegmark
The power of deeper networks for expressing natural functions. CoRR (2017)
Ben Garfinkel, Miles Brundage, Daniel Filan, Carrick Flynn, Jelena Luketina, Michael Page, Anders Sandberg, Andrew Snyder-Beattie, Max Tegmark
On the Impossibility of Supersized Machines. CoRR (2017)
Henry W. Lin, Max Tegmark
Critical Behavior in Physics and Probabilistic Formal Languages. Entropy 19 (7) (2017)
Henry Lin, Max Tegmark
Critical Behavior from Deep Dynamics: A Hidden Dimension in Natural Language. CoRR (2016)
Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Max Tegmark, Marin Soljacic
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNN. CoRR (2016)
Max Tegmark
Improved Measures of Integrated Information. PLoS Comput. Biol. 12 (11) (2016)
Henry W. Lin, Max Tegmark
Why does deep and cheap learning work so well? CoRR (2016)
Stuart J. Russell, Daniel Dewey, Max Tegmark
Research Priorities for Robust and Beneficial Artificial Intelligence. CoRR (2016)
Stuart J. Russell, Daniel Dewey, Max Tegmark
Research Priorities for Robust and Beneficial Artificial Intelligence. AI Mag. 36 (4) (2015)
Max Tegmark
Nuclear War from a Cosmic Perspective. CoRR (2015)
Max Tegmark
Friendly Artificial Intelligence: The Physics Challenge. AAAI Workshop: AI and Ethics (2015)
Max Tegmark
Friendly Artificial Intelligence: the Physics Challenge. CoRR (2014)
Max Tegmark
Why the brain is probably not a quantum computer. Inf. Sci. 128 (3-4) (2000)
Max Tegmark
The importance of quantum decoherence in brain processes CoRR (1999)
Harold S. Shapiro, Max Tegmark
An Elementary Proof That the Biharmonic Green Function of an Eccentric Ellipse Changes Sign. SIAM Rev. 36 (1) (1994)