Lenka Zdeborová
Associate Professor
Leads the Statistical Physics of Computation Laboratory, using statistical physics to study high-dimensional learning and inference problems.
Lenka Zdeborová's lab at EPFL works on learning theory & optimization, signal processing & information theory and efficient training & inference. 43 papers since 2023, 18 at top venues, mostly NeurIPS and ICML. 5 PhD students. Applications close .
At a glance
- papers, 2023–2026
- 11/ year
- at T1 venues
- 42%
- PhD students
- 5
- MS students
- 0
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 3 papers2026 · T1 0 · collecting
- 20 papers2025 · T1 10
- 17 papers2024 · T1 7
- 3 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, ICML, UAI, AISTATS, COLT
Research focuspaper titles that use each topic's words
- Learning theory & optimization12 papers
- Signal processing & information theory2 papers
- Efficient training & inference2 papers
- statistical physics1 paper
- physics1 paper
Paper list
From the lab homepage.
20263 papers
- Physical Review EInference in spreading processes with neural-network priors (opens in a new tab)
- Physical Review EMinority takeover in majority dynamics: Searching for rare initializations via the history passing algorithm (opens in a new tab)
- SciPost PhysicsThe maximum-average subtensor problem: Equilibrium and out-of-equilibrium properties (opens in a new tab)
202520 papers
- Journal of Statistical Mechanics: Theory and ExperimentA phase transition between positional and semantic learning in a solvable model of dot-product attention (opens in a new tab)
- NeurIPS (T1)Asymptotics of SGD in Sequence-Single Index Models and Single-Layer Attention Networks
- NeurIPS (T1)Bayes optimal learning of attention-indexed models
- JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENTBayes-optimal learning of deep random networks of extensive-width* (opens in a new tab)
- PRXBilinear Sequence Regression: A Model for Learning from Long Sequences of High-Dimensional Tokens (opens in a new tab)
- UAI (T1)Building Conformal Prediction Intervals with Approximate Message Passing (opens in a new tab)
- ICML (T1)Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers (opens in a new tab)
- Physical Review EDynamical cavity method for hypergraphs and its application to quenches in the k-XOR-SAT problem (opens in a new tab)
- Communications in Mathematical PhysicsEstimating Rank-One Matrices with Mismatched Prior and Noise: Universality and Large Deviations (opens in a new tab)
- AISTATS (T1)Fundamental computational limits of weak learnability in high-dimensional multi-index models (opens in a new tab)
- ICML (T1)Fundamental limits of learning in sequence multi-index models and deep attention networks: high-dimensional asymptotics and sharp thresholds (opens in a new tab)
- COLT (T1)Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications
202417 papers
- UAI (T1)Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression
- ICLR (T1)Analysis of Learning a Flow-Based Generative Model From Limited Sample Complexity
- The Third Learning On Graphs ConferenceAsymptotic generalization error of a single-layer graph convolutional network (opens in a new tab)
- ICML (T1)Asymptotics of feature learning in two-layer networks after one gradient-step
- NeurIPS (T1)Bayes-optimal learning of an extensive-width neural network from quadratically many samples (opens in a new tab)
- Journal of Physics A: Mathematical and TheoreticalCounting and hardness-of-finding fixed points in cellular automata on random graphs (opens in a new tab)
- Physical Review EDynamical phase transitions in graph cellular automata (opens in a new tab)
- Physical Review EGaussian universality of perceptrons with random labels (opens in a new tab)
- Journal of Physics A: Mathematical and TheoreticalGibbs sampling the posterior of neural networks (opens in a new tab)
- JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENTLes Houches 2022 Special Issue: Editorial (opens in a new tab)
- Journal of Physics A: Mathematical and TheoreticalOn the atypical solutions of the symmetric binary perceptron (opens in a new tab)
- TMLR (T1)Optimal Inference in Contextual Stochastic Block Models
20233 papers
- NeurIPS (T1)High-dimensional Asymptotics of Denoising Autoencoders
- Journal Of Statistical Mechanics-Theory And ExperimentMulti-layer state evolution under random convolutional design (opens in a new tab)
- Journal Of Statistical Mechanics-Theory And ExperimentPhase diagram of stochastic gradient descent in high-dimensional two-layer neural networks (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to EPFLFall 2027
EDIC Computer and Communication Sciences PhD
- Round
- Round 1
- Opens
- —
- GRE
- optional
- English
- TOEFL 100 / IELTS 7.0
- Fee
- none
Confirmed on the program page.
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Data
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