Max Tegmark - RankMe

115 papers A* 14A 1Journal 96Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Decision-Theoretic Formalisation of Steganography With Applications to LLM Monitoring. CoRR Usman Anwar, Julianna Piskorz, David D. Baek, David Africa, James Weatherall, Max Tegmark, Christian Schroeder de Witt, Mihaela van der Schaar, David Krueger
2025	J	`jnl`	A Definition of AGI. CoRR Dan Hendrycks, Dawn Song, Christian Szegedy, Honglak Lee, Yarin Gal, Erik Brynjolfsson, Sharon Li, Andy Zou, Lionel Levine, Bo Han, Jie Fu, Ziwei Liu, Jinwoo Shin, Kimin Lee, Mantas Mazeika, Long Phan, George Ingebretsen, Adam Khoja, Cihang Xie, Olawale Salaudeen, Matthias Hein, Kevin Zhao, Alexander Pan, David Duvenaud, Bo Li, Steve Omohundro, Gabriel Alfour, Max Tegmark, Kevin McGrew, Gary Marcus, Jaan Tallinn, Eric Schmidt, Yoshua Bengio
2025	J	`jnl`	A benchmark for vericoding: formally verified program synthesis. CoRR Sergiu Bursuc, Theodore Ehrenborg, Shaowei Lin, Lacramioara Astefanoaei, Ionel Emilian Chiosa, Jure Kukovec, Alok Singh, Oliver Butterley, Adem Bizid, Quinn Dougherty, Miranda Zhao, Max Tan, Max Tegmark
2025	A*	`conf`	Are Sparse Autoencoders Useful? A Case Study in Sparse Probing. ICML Subhash Kantamneni, Joshua Engels, Senthooran Rajamanoharan, Max Tegmark, Neel Nanda
2025	J	`jnl`	Are Sparse Autoencoders Useful? A Case Study in Sparse Probing. CoRR Subhash Kantamneni, Joshua Engels, Senthooran Rajamanoharan, Max Tegmark, Neel Nanda
2025	J	`jnl`	DafnyBench: A Benchmark for Formal Software Verification. Trans. Mach. Learn. Res. Chloe Loughridge, Qinyi Sun, Seth Ahrenbach, Federico Cassano, Chuyue Sun, Ying Sheng, Anish Mudide, Md Rakib Hossain Misu, Nada Amin, Max Tegmark
2025	J	`jnl`	Decomposing The Dark Matter of Sparse Autoencoders. Trans. Mach. Learn. Res. Joshua Engels, Logan Riggs Smith, Max Tegmark
2025	J	`jnl`	Dense SAE Latents Are Features, Not Bugs. CoRR Xiaoqing Sun, Alessandro Stolfo, Joshua Engels, Ben Wu, Senthooran Rajamanoharan, Mrinmaya Sachan, Max Tegmark
2025	J	`jnl`	Do Two AI Scientists Agree? CoRR Xinghong Fu, Ziming Liu, Max Tegmark
2025	A*	`conf`	Efficient Dictionary Learning with Switch Sparse Autoencoders. ICLR Anish Mudide, Joshua Engels, Eric J. Michaud, Max Tegmark, Christian Schröder de Witt
2025	J	`jnl`	Harmonic Loss Trains Interpretable AI Models. CoRR David D. Baek, Ziming Liu, Riya Tyagi, Max Tegmark
2025	J	`jnl`	Harmonic Loss Trains Interpretable AI Models. Trans. Mach. Learn. Res. David D. Baek, Ziming Liu, Riya Tyagi, Max Tegmark
2025	A*	`conf`	KAN: Kolmogorov-Arnold Networks. ICLR Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson, Marin Soljacic, Thomas Y. Hou, Max Tegmark
2025	J	`jnl`	Language Models Use Trigonometry to Do Addition. CoRR Subhash Kantamneni, Max Tegmark
2025	A*	`conf`	Low-Rank Adapting Models for Sparse Autoencoders. ICML Matthew Chen, Joshua Engels, Max Tegmark
2025	J	`jnl`	Low-Rank Adapting Models for Sparse Autoencoders. CoRR Matthew Chen, Joshua Engels, Max Tegmark
2025	J	`jnl`	Neural Thermodynamic Laws for Large Language Model Training. CoRR Ziming Liu, Yizhou Liu, Jeff Gore, Max Tegmark
2025	A*	`conf`	Not All Language Model Features Are One-Dimensionally Linear. ICLR Joshua Engels, Eric J. Michaud, Isaac Liao, Wes Gurnee, Max Tegmark
2025	J	`jnl`	On the creation of narrow AI: hierarchy and nonlocality of neural network skills. CoRR Eric J. Michaud, Asher Parker-Sartori, Max Tegmark
2025	J	`jnl`	Open Problems in Mechanistic Interpretability. CoRR Lee Sharkey, Bilal Chughtai, Joshua Batson, Jack Lindsey, Jeff Wu, Lucius Bushnaq, Nicholas Goldowsky-Dill, Stefan Heimersheim, Alejandro Ortega, Joseph Isaac Bloom, Stella Biderman, Adrià Garriga-Alonso, Arthur Conmy, Neel Nanda, Jessica Rumbelow, Martin Wattenberg, Nandi Schoots, Joseph Miller, Eric J. Michaud, Stephen Casper, Max Tegmark, William Saunders, David Bau, Eric Todd, Atticus Geiger, Mor Geva, Jesse Hoogland, Daniel Murfet, Tom McGrath
2025	J	`jnl`	Open Problems in Mechanistic Interpretability. Trans. Mach. Learn. Res. Lee Sharkey, Bilal Chughtai, Joshua Batson, Jack Lindsey, Jeffrey Wu, Lucius Bushnaq, Nicholas Goldowsky-Dill, Stefan Heimersheim, Alejandro Ortega, Joseph Isaac Bloom, Stella Biderman, Adrià Garriga-Alonso, Arthur Conmy, Neel Nanda, Jessica Rumbelow, Martin Wattenberg, Nandi Schoots, Joseph Miller, William Saunders, Eric J. Michaud, Stephen Casper, Max Tegmark, David Bau, Eric Todd, Atticus Geiger, Mor Geva, Jesse Hoogland, Daniel Murfet, Tom McGrath
2025	J	`jnl`	Physics of Skill Learning. CoRR Ziming Liu, Yizhou Liu, Eric J. Michaud, Jeff Gore, Max Tegmark
2025	J	`jnl`	Scaling Laws For Scalable Oversight. CoRR Joshua Engels, David D. Baek, Subhash Kantamneni, Max Tegmark
2025	J	`jnl`	The Geometry of Concepts: Sparse Autoencoder Feature Structure. Entropy Yuxiao Li, Eric J. Michaud, David D. Baek, Joshua Engels, Xiaoqing Sun, Max Tegmark
2025	J	`jnl`	The Singapore Consensus on Global AI Safety Research Priorities. CoRR Yoshua Bengio, Tegan Maharaj, Luke Ong, Stuart Russell, Dawn Song, Max Tegmark, Lan Xue, Ya-Qin Zhang, Stephen Casper, Wan Sie Lee, Sören Mindermann, Vanessa Wilfred, Vidhisha Balachandran, Fazl Barez, Michael Belinsky, Imane Bello, Malo Bourgon, Mark Brakel, Siméon Campos, Duncan Cass-Beggs, Jiahao Chen, Rumman Chowdhury, Kuan Chua Seah, Jeff Clune, Juntao Dai, Agnès Delaborde, Nouha Dziri, Francisco Eiras, Joshua Engels, Jinyu Fan, Adam Gleave, Noah Goodman, Fynn Heide, Johannes Heidecke, Dan Hendrycks, Cyrus Hodes, Bryan Low Kian Hsiang, Minlie Huang, Sami Jawhar, Wang Jingyu, Adam Tauman Kalai, Meindert Kamphuis, Mohan S. Kankanhalli, Subhash Kantamneni, Mathias Bonde Kirk, Thomas Kwa, Jeffrey Ladish, Kwok-Yan Lam, Wan Lee Sie, Taewhi Lee, Xiaojian Li, Jiajun Liu, Chaochao Lu, Yifan Mai, Richard Mallah, Julian Michael, Nick Moës, Simon Möller, Kihyuk Nam, Kwan Yee Ng, Mark Nitzberg, Besmira Nushi, Seán Ó hÉigeartaigh, Alejandro Ortega, Pierre Peigné, James Petrie, Benjamin Prud'homme, Reihaneh Rabbany, Nayat Sánchez-Pi, Sarah Schwettmann, Buck Shlegeris, Saad Siddiqui, Aradhana Sinha, Martín Soto, Cheston Tan, Dong Ting, William-Chandra Tjhi, Robert Trager, Brian Tse, Anthony Tung K. H., John Willes, Denise Wong, Wei Xu, Rongwu Xu, Yi Zeng, HongJiang Zhang, Djordje Zikelic
2025	J	`jnl`	Towards Understanding Distilled Reasoning Models: A Representational Approach. CoRR David D. Baek, Max Tegmark
2024	J	`jnl`	A Resource Model For Neural Scaling Law. CoRR Jinyeop Song, Ziming Liu, Max Tegmark, Jeff Gore
2024	—	`conf`	Black-Box Access is Insufficient for Rigorous AI Audits. FAccT 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
2024	J	`jnl`	Black-Box Access is Insufficient for Rigorous AI Audits. CoRR 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
2024	J	`jnl`	DafnyBench: A Benchmark for Formal Software Verification. CoRR Chloe Loughridge, Qinyi Sun, Seth Ahrenbach, Federico Cassano, Chuyue Sun, Ying Sheng, Anish Mudide, Md Rakib Hossain Misu, Nada Amin, Max Tegmark
2024	J	`jnl`	Decomposing The Dark Matter of Sparse Autoencoders. CoRR Joshua Engels, Logan Riggs Smith, Max Tegmark
2024	J	`jnl`	Efficient Dictionary Learning with Switch Sparse Autoencoders. CoRR Anish Mudide, Joshua Engels, Eric J. Michaud, Max Tegmark, Christian Schröder de Witt
2024	J	`jnl`	GenEFT: Understanding Statics and Dynamics of Model Generalization via Effective Theory. CoRR David D. Baek, Ziming Liu, Max Tegmark
2024	J	`jnl`	Generalization from Starvation: Hints of Universality in LLM Knowledge Graph Learning. CoRR David D. Baek, Yuxiao Li, Max Tegmark
2024	J	`jnl`	How Do Transformers "Do" Physics? Investigating the Simple Harmonic Oscillator. CoRR Subhash Kantamneni, Ziming Liu, Max Tegmark
2024	J	`jnl`	How Do Transformers Model Physics? Investigating the Simple Harmonic Oscillator. Entropy Subhash Kantamneni, Ziming Liu, Max Tegmark
2024	J	`jnl`	KAN 2.0: Kolmogorov-Arnold Networks Meet Science. CoRR Ziming Liu, Pingchuan Ma, Yixuan Wang, Wojciech Matusik, Max Tegmark
2024	J	`jnl`	KAN: Kolmogorov-Arnold Networks. CoRR Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson, Marin Soljacic, Thomas Y. Hou, Max Tegmark
2024	A*	`conf`	Language Models Represent Space and Time. ICLR Wes Gurnee, Max Tegmark
2024	J	`jnl`	Not All Language Model Features Are Linear. CoRR Joshua Engels, Isaac Liao, Eric J. Michaud, Wes Gurnee, Max Tegmark
2024	J	`jnl`	Opening the AI Black Box: Distilling Machine-Learned Algorithms into Code. Entropy Eric J. Michaud, Isaac Liao, Vedang Lad, Ziming Liu, Anish Mudide, Chloe Loughridge, Zifan Carl Guo, Tara Rezaei Kheirkhah, Mateja Vukelic, Max Tegmark
2024	J	`jnl`	Opening the AI black box: program synthesis via mechanistic interpretability. CoRR Eric J. Michaud, Isaac Liao, Vedang Lad, Ziming Liu, Anish Mudide, Chloe Loughridge, Zifan Carl Guo, Tara Rezaei Kheirkhah, Mateja Vukelic, Max Tegmark
2024	J	`jnl`	OptPDE: Discovering Novel Integrable Systems via AI-Human Collaboration. CoRR Subhash Kantamneni, Ziming Liu, Max Tegmark
2024	J	`jnl`	Seeing Is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability. Entropy Ziming Liu, Eric Gan, Max Tegmark
2024	J	`jnl`	Survival of the Fittest Representation: A Case Study with Modular Addition. CoRR Xiaoman Delores Ding, Zifan Carl Guo, Eric J. Michaud, Ziming Liu, Max Tegmark
2024	J	`jnl`	The Geometry of Concepts: Sparse Autoencoder Feature Structure. CoRR Yuxiao Li, Eric J. Michaud, David D. Baek, Joshua Engels, Xiaoqing Sun, Max Tegmark
2024	J	`jnl`	The Remarkable Robustness of LLMs: Stages of Inference? CoRR Vedang Lad, Wes Gurnee, Max Tegmark
2024	J	`jnl`	Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. CoRR David Dalrymple, Joar Skalse, Yoshua Bengio, Stuart Russell, Max Tegmark, Sanjit A. Seshia, Steve Omohundro, Christian Szegedy, Ben Goldhaber, Nora Ammann, Alessandro Abate, Joe Halpern, Clark W. Barrett, Ding Zhao, Tan Zhi-Xuan, Jeannette M. Wing, Joshua B. Tenenbaum
2023	J	`jnl`	A Neural Scaling Law from Lottery Ticket Ensembling. CoRR Ziming Liu, Max Tegmark
2023	J	`jnl`	Discovering New Interpretable Conservation Laws as Sparse Invariants. CoRR Ziming Liu, Patrick Obin Sturm, Saketh Bharadwaj, Sam Silva, Max Tegmark
2023	J	`jnl`	Divide-and-Conquer Dynamics in AI-Driven Disempowerment. CoRR Peter S. Park, Max Tegmark
2023	J	`jnl`	GenPhys: From Physical Processes to Generative Models. CoRR Ziming Liu, Di Luo, Yilun Xu, Tommi S. Jaakkola, Max Tegmark
2023	J	`jnl`	Generating Interpretable Networks using Hypernetworks. CoRR Isaac Liao, Ziming Liu, Max Tegmark
2023	J	`jnl`	Grokking as Compression: A Nonlinear Complexity Perspective. CoRR Ziming Liu, Ziqian Zhong, Max Tegmark
2023	J	`jnl`	Growing Brains: Co-emergence of Anatomical and Functional Modularity in Recurrent Neural Networks. CoRR Ziming Liu, Mikail Khona, Ila R. Fiete, Max Tegmark
2023	J	`jnl`	Language Models Represent Space and Time. CoRR Wes Gurnee, Max Tegmark
2023	A*	`conf`	Omnigrok: Grokking Beyond Algorithmic Data. ICLR Ziming Liu, Eric J. Michaud, Max Tegmark
2023	A*	`conf`	PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. ICML Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola
2023	J	`jnl`	PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. CoRR Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola
2023	J	`jnl`	Precision Machine Learning. Entropy Eric J. Michaud, Ziming Liu, Max Tegmark
2023	J	`jnl`	Provably safe systems: the only path to controllable AGI. CoRR Max Tegmark, Steve Omohundro
2023	J	`jnl`	Seeing is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability. CoRR Ziming Liu, Eric Gan, Max Tegmark
2023	A*	`conf`	The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks. NeurIPS Ziqian Zhong, Ziming Liu, Max Tegmark, Jacob Andreas
2023	J	`jnl`	The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks. CoRR Ziqian Zhong, Ziming Liu, Max Tegmark, Jacob Andreas
2023	J	`jnl`	The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets. CoRR Samuel Marks, Max Tegmark
2023	A*	`conf`	The Quantization Model of Neural Scaling. NeurIPS Eric J. Michaud, Ziming Liu, Uzay Girit, Max Tegmark
2023	J	`jnl`	The Quantization Model of Neural Scaling. CoRR Eric J. Michaud, Ziming Liu, Uzay Girit, Max Tegmark
2022	J	`jnl`	AI Poincaré 2.0: Machine Learning Conservation Laws from Differential Equations. CoRR Ziming Liu, Varun Madhavan, Max Tegmark
2022	J	`jnl`	Biological error correction codes generate fault-tolerant neural networks. CoRR Alexander Zlokapa, Andrew K. Tan, John M. Martyn, Max Tegmark, Isaac L. Chuang
2022	J	`jnl`	Omnigrok: Grokking Beyond Algorithmic Data. CoRR Ziming Liu, Eric J. Michaud, Max Tegmark
2022	J	`jnl`	Pareto-Optimal Clustering with the Primal Deterministic Information Bottleneck. Entropy Andrew K. Tan, Max Tegmark, Isaac L. Chuang
2022	J	`jnl`	Pareto-optimal clustering with the primal deterministic information bottleneck. CoRR Andrew K. Tan, Max Tegmark, Isaac L. Chuang
2022	A*	`conf`	Poisson Flow Generative Models. NeurIPS Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola
2022	J	`jnl`	Poisson Flow Generative Models. CoRR Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola
2022	J	`jnl`	Precision Machine Learning. CoRR Eric J. Michaud, Ziming Liu, Max Tegmark
2022	J	`jnl`	Toward a more accurate 3D atlas of C. elegans neurons. BMC Bioinform. Michael Skuhersky, Tailin Wu, Eviatar Yemini, Amin Nejatbakhsh, Edward S. Boyden, Max Tegmark
2022	A*	`conf`	Towards Understanding Grokking: An Effective Theory of Representation Learning. NeurIPS Ziming Liu, Ouail Kitouni, Niklas Nolte, Eric J. Michaud, Max Tegmark, Mike Williams
2022	J	`jnl`	Towards Understanding Grokking: An Effective Theory of Representation Learning. CoRR Ziming Liu, Ouail Kitouni, Niklas Nolte, Eric J. Michaud, Max Tegmark, Mike Williams
2021	J	`jnl`	Machine-Learning Non-Conservative Dynamics for New-Physics Detection. CoRR Ziming Liu, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu
2021	J	`jnl`	Machine-Learning media bias. CoRR Samantha D'Alonzo, Max Tegmark
2021	J	`jnl`	Machine-learning hidden symmetries. CoRR Ziming Liu, Max Tegmark
2021	J	`jnl`	Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning. CoRR Ziming Liu, Yunyue Chen, Yuanqi Du, Max Tegmark
2020	A*	`conf`	AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity. NeurIPS Silviu-Marian Udrescu, Andrew K. Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark
2020	J	`jnl`	AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity. CoRR Silviu-Marian Udrescu, Andrew K. Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark
2020	J	`jnl`	AI Poincaré: Machine Learning Conservation Laws from Trajectories. CoRR Ziming Liu, Max Tegmark
2020	J	`jnl`	Pareto-Optimal Data Compression for Binary Classification Tasks. Entropy Max Tegmark, Tailin Wu
2020	J	`jnl`	Symbolic Pregression: Discovering Physical Laws from Raw Distorted Video. CoRR Silviu-Marian Udrescu, Max Tegmark
2019	J	`jnl`	AI Feynman: a Physics-Inspired Method for Symbolic Regression. CoRR Silviu-Marian Udrescu, Max Tegmark
2019	J	`jnl`	Gated Orthogonal Recurrent Units: On Learning to Forget. Neural Comput. Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
2019	A	`conf`	Learnability for the Information Bottleneck. UAI Tailin Wu, Ian S. Fischer, Isaac L. Chuang, Max Tegmark
2019	J	`jnl`	Learnability for the Information Bottleneck. CoRR Tailin Wu, Ian S. Fischer, Isaac L. Chuang, Max Tegmark
2019	J	`jnl`	Learnability for the Information Bottleneck. Entropy Tailin Wu, Ian S. Fischer, Isaac L. Chuang, Max Tegmark
2019	J	`jnl`	Pareto-optimal data compression for binary classification tasks. CoRR Max Tegmark, Tailin Wu
2019	J	`jnl`	The role of artificial intelligence in achieving the Sustainable Development Goals. CoRR Ricardo Vinuesa, Hossein Azizpour, Iolanda Leite, Madeline Balaam, Virginia Dignum, Sami Domisch, Anna Felländer, Simone Langhans, Max Tegmark, Francesco Fuso Nerini
2018	—	`conf`	Gated Orthogonal Recurrent Units: On Learning to Forget. AAAI Workshops Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
2018	J	`jnl`	Meta-learning autoencoders for few-shot prediction. CoRR Tailin Wu, John Peurifoy, Isaac L. Chuang, Max Tegmark
2018	—	`conf`	The power of deeper networks for expressing natural functions. ICLR (Poster) David Rolnick, Max Tegmark
2018	J	`jnl`	Toward an AI Physicist for Unsupervised Learning. CoRR Tailin Wu, Max Tegmark
2017	J	`jnl`	Critical Behavior in Physics and Probabilistic Formal Languages. Entropy Henry W. Lin, Max Tegmark
2017	J	`jnl`	Gated Orthogonal Recurrent Units: On Learning to Forget. CoRR Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
2017	J	`jnl`	On the Impossibility of Supersized Machines. CoRR Ben Garfinkel, Miles Brundage, Daniel Filan, Carrick Flynn, Jelena Luketina, Michael Page, Anders Sandberg, Andrew Snyder-Beattie, Max Tegmark
2017	J	`jnl`	The power of deeper networks for expressing natural functions. CoRR David Rolnick, Max Tegmark
2017	A*	`conf`	Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs. ICML Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Yann LeCun, Max Tegmark, Marin Soljacic
2016	J	`jnl`	Critical Behavior from Deep Dynamics: A Hidden Dimension in Natural Language. CoRR Henry Lin, Max Tegmark
2016	J	`jnl`	Improved Measures of Integrated Information. PLoS Comput. Biol. Max Tegmark
2016	J	`jnl`	Research Priorities for Robust and Beneficial Artificial Intelligence. CoRR Stuart Russell, Daniel Dewey, Max Tegmark
2016	J	`jnl`	Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNN. CoRR Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Max Tegmark, Marin Soljacic
2016	J	`jnl`	Why does deep and cheap learning work so well? CoRR Henry W. Lin, Max Tegmark
2015	—	`conf`	Friendly Artificial Intelligence: The Physics Challenge. AAAI Workshop: AI and Ethics Max Tegmark
2015	J	`jnl`	Nuclear War from a Cosmic Perspective. CoRR Max Tegmark
2015	J	`jnl`	Research Priorities for Robust and Beneficial Artificial Intelligence. AI Mag. Stuart Russell, Daniel Dewey, Max Tegmark
2014	J	`jnl`	Friendly Artificial Intelligence: the Physics Challenge. CoRR Max Tegmark
2000	J	`jnl`	Why the brain is probably not a quantum computer. Inf. Sci. Max Tegmark
1999	J	`jnl`	The importance of quantum decoherence in brain processes CoRR Max Tegmark
1994	J	`jnl`	An Elementary Proof That the Biharmonic Green Function of an Eccentric Ellipse Changes Sign. SIAM Rev. Harold S. Shapiro, Max Tegmark