Max Tegmark
16 papers · 2017–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (8) π Conference Polyglot (4) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (12)
π§
Keyword Pioneer
π
Cross-Pollinator
(12)
π
Conference Polyglot
(4)
π
Triple Crown
π
Century Club
(16)
β‘
Prolific Year
(5)
π
Conference Pioneer
β
The Questioner
Conferences
ICLR (6)
NIPS (5)
ICML (4)
UAI (1)
Top co-authors
Keywords
generative model
(2)
neural network
(2)
poisson flow
(2)
normalizing flow
(2)
representation learning
(2)
graph modularity
(1)
hypothesis testing
(1)
information bottleneck
(1)
long short-term memory
(1)
phase transition
(1)
recurrent neural network
(1)
in-context learning
(1)
latent space
(1)
mechanistic interpretability
(1)
algorithm discovery
(1)
symbolic regression
(1)
ordinary differential equation
(1)
pareto optimal
(1)
physics-inspired model
(1)
diffusion model
(1)
Papers
Low-Rank Adapting Models for Sparse Autoencoders
ICML 2025
KAN: KolmogorovβArnold Networks
ICLR 2025
Not All Language Model Features Are One-Dimensionally Linear
ICLR 2025
Efficient Dictionary Learning with Switch Sparse Autoencoders
ICLR 2025
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
ICML 2025
Language Models Represent Space and Time
ICLR 2024
Omnigrok: Grokking Beyond Algorithmic Data
ICLR 2023
The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks
NIPS 2023
The Quantization Model of Neural Scaling
NIPS 2023
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models
ICML 2023
Towards Understanding Grokking: An Effective Theory of Representation Learning
NIPS 2022
Poisson Flow Generative Models
NIPS 2022
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
NIPS 2020
Learnability for the Information Bottleneck
UAI 2019
The power of deeper networks for expressing natural functions
ICLR 2018
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
ICML 2017