Tegmark, Max

THE SEVENTH DATA RELEASE OF THE SLOAN DIGITAL SKY SURVEY

Abazajian, K. N., Adelman-McCarthy, J. K., Agüeros, M. A., Allam, S. S., Prieto, C. A., An, D., Anderson, K. S. J., Anderson, S. F., Annis, J., Bahcall, N. A., et al. (2009) · The Astrophysical Journal Supplement Series

Galaxies: Formation, Evolution, PhenomenaAstronomy and Astrophysical Research

Cited by 5,341

The role of artificial intelligence in achieving the Sustainable Development Goals

Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F. (2020) · Nature Communications

Ethics and Social Impacts of AIInnovation, Sustainability, Human-Machine Systems

Cited by 3,294

Baryon acoustic oscillations in the Sloan Digital Sky Survey Data Release 7 galaxy sample

Percival, W. J., Reid, B. A., Eisenstein, D. J., Bahcall, N. A., Budavari, T., Frieman, J. A., Fukugita, M., Gunn, J. E., Ivezić, Ž., Knapp, G. R., et al. (2010) · Monthly Notices of the Royal Astronomical Society

Cosmology and Gravitation TheoriesGalaxies: Formation, Evolution, Phenomena

Cited by 1,846

The Sixth Data Release of the Sloan Digital Sky Survey

Adelman‐McCarthy, J. K., Agüeros, M. A., Allam, S. S., Allende Prieto, C., Anderson, K. S. J., Anderson, S. F., Annis, J., Bahcall, N. A., Bailer‐Jones, C. A. L., Baldry, I. K., et al. (2008) · The Astrophysical Journal Supplement Series

Galaxies: Formation, Evolution, PhenomenaAstronomy and Astrophysical Research

Cited by 1,486

Importance of quantum decoherence in brain processes

Tegmark, M. (2000) · Physical Review E

Quantum Mechanics and ApplicationsPhilosophy and Theoretical Science

Cited by 776

Significance of the largest scale CMB fluctuations in WMAP

de Oliveira-Costa, A., Tegmark, M., Zaldarriaga, M., & Hamilton, A. (2004) · Physical Review D

Cosmology and Gravitation TheoriesNoncommutative and Quantum Gravity Theories

Cited by 651

Research Priorities for Robust and Beneficial Artificial Intelligence

Russell, S., Dewey, D., & Tegmark, M. (2015) · AI Magazine

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 637

Dimensionless constants, cosmology, and other dark matters

Tegmark, M., Aguirre, A., Rees, M. J., & Wilczek, F. (2006) · Physical Review D

Dark Matter and Cosmic PhenomenaCosmology and Gravitation Theories

Cited by 401

Why Does Deep and Cheap Learning Work So Well?

Lin, H. W., Tegmark, M., & Rolnick, D. (2017) · Journal of Statistical Physics

Neural Networks and ApplicationsStochastic Gradient Optimization Techniques

Cited by 393

Open Problems in Mechanistic Interpretability

Sharkey, L., Chughtai, B., Batson, J., Lindsey, J., Wu, J., Bushnaq, L., Goldowsky-Dill, N., Heimersheim, S., Ortega, A., Bloom, J., et al. (2025) · arXiv

Explainable Artificial Intelligence (XAI)Neural Networks and Applications

Cited by 291

What does inflation really predict?

Tegmark, M. (2005) · Journal of Cosmology and Astroparticle Physics

Cosmology and Gravitation TheoriesNoncommutative and Quantum Gravity Theories

Cited by 216

Consciousness as a state of matter

Tegmark, M. (2015) · Chaos, Solitons & Fractals

Philosophy and Theoretical ScienceQuantum Mechanics and Applications

Cited by 183

Why Is the Cosmic Microwave Background Fluctuation Level 10−5?

Tegmark, M., & Rees, M. J. (1998) · The Astrophysical Journal

Cosmology and Gravitation TheoriesGalaxies: Formation, Evolution, Phenomena

Cited by 159

Parallel Universes

Tegmark, M. (2003) · Scientific American

Cosmology and Gravitation TheoriesBlack Holes and Theoretical Physics

Cited by 143

Angular Clustering with Photometric Redshifts in the Sloan Digital Sky Survey: Bimodality in the Clustering Properties of Galaxies

Budavari, T., Connolly, A. J., Szalay, A. S., Szapudi, I., Csabai, I., Scranton, R., Bahcall, N. A., Brinkmann, J., Eisenstein, D. J., Frieman, J. A., et al. (2003) · The Astrophysical Journal

Galaxies: Formation, Evolution, PhenomenaCosmology and Gravitation Theories

Cited by 135

On the dimensionality of spacetime

Tegmark, M. (1997) · Classical and Quantum Gravity

Black Holes and Theoretical PhysicsNoncommutative and Quantum Gravity Theories

Cited by 135

Improved measures of integrated information

Tegmark, M. (2016) · PLOS Computational Biology

Complex Systems and DynamicsFunctional Brain Connectivity Studies

Cited by 128

Toward an artificial intelligence physicist for unsupervised learning

Wu, T., & Tegmark, M. (2019) · Physical Review E

Model Reduction and Neural NetworksNeural Networks and Applications

Cited by 99

Apparent wave function collapse caused by scattering

Tegmark, M. (1993) · Foundations of Physics Letters

Quantum Mechanics and ApplicationsNoncommutative and Quantum Gravity Theories

Cited by 87

Machine learning conservation laws from differential equations

Liu, Z., Madhavan, V., & Tegmark, M. (2022) · Physical Review E

Model Reduction and Neural NetworksNumerical Solvers for Ordinary Differential Equations

Cited by 77

The Quantization Model of Neural Scaling

Michaud, E. J., Liu, Z., Girit, U., & Tegmark, M. (2023) · arXiv

Topic ModelingNeural Networks and Applications

Cited by 57

Language Models Represent Space and Time

Gurnee, W., & Tegmark, M. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 46

Opening the AI Black Box: Distilling Machine-Learned Algorithms into Code

Michaud, E. J., Liao, I., Lad, V., Liu, Z., Mudide, A., Loughridge, C., Guo, Z. C., Kheirkhah, T. R., Vukelić, M., & Tegmark, M. (2024) · Entropy

Explainable Artificial Intelligence (XAI)Software Engineering Research

Cited by 30

The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Marks, S., & Tegmark, M. (2023) · arXiv

Topic ModelingExplainable Artificial Intelligence (XAI)

Cited by 21