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Our work on how LLMs store relations selected as NeurIPS Spotlight paper
Our paper The Structure of Relation Decoding Linear Operators in Large Language Models by Miranda Anna Christ, Adrián Csiszárik, Gergely Becsó, and Dániel Varga was accepted at the NeurIPS 2025 conference as a Spotlight paper (~3% of submissions).
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Healthcare

Prevention & Prediction

Patient Pathways

Patient Pathway Mission
Leveraging Hungary’s healthcare data assets for prevention, prediction, and decision support.
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Diverse beam search to find densest-known planar unit distance graphs

Publication
June 13, 2025
publications
This paper addresses the problem of determining the maximum number of edges in a unit distance graph (UDG) of n vertices using computer search. An unsolved problem of Paul Erdős asks the maximum number of edges 𝑢⁡(𝑛) a UDG of n vertices can have. Those UDGs that attain 𝑢⁡(𝑛) are called “maximally dense.” In this paper, we seek to demonstrate a computer algorithm to generate dense UDGs for vertex counts up to at least 100.
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June 13, 2025

Zsolt Zombori

Better Exploration for Symbolic Supervision

Blog Post
June 2, 2025
posts
Despite the tremendous success that deep learning has shown in the past decade, there are certain application domains for which deep learning has traditionally been considered as not suitable. In particular, deep learning is notoriously known to be very data inefficient and to provide no guarantees with respect to the behaviour of the trained system. As a result of these limitations, the usage of neural networks in small data and safety critical domains has so far remained rather restricted.
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June 2, 2025

Piercing intersecting convex sets

Publication
April 1, 2025
publications
Assume two finite families A and B of convex sets in R3 have the property that A ∩ B ≠ ∅ for every A ∈ A and B∈B. Is there a constant γ > 0 (independent of A and B) such that there is a line intersecting γ|A| sets in A or γ|B| sets in B? This is an intriguing Helly-type question from a paper by Martínez, Roldan and Rubin. We confirm this in the special case when all sets in A lie in parallel planes and all sets in B lie in parallel planes; in fact, one of the two families has a transversal by a single line.
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April 1, 2025

Közelebb a matematikához - Varga Dániel a HUN-REN Rényi Alfréd Matematikai Kutatóintézet matematikusa

Podcast
March 11, 2025
podcasts
Agyműtéteket végez Mesterséges Intelligenciákon a Közelebb a matematikához vendége, hogy azok működéséről az AI kutatócsoport tagja minél több információhoz juthassanak. Varga Dániel ugyanis a HUN-REN Rényi Alfréd Matematikai Kutatóintézet szakembere, programozó matematikus, aki az interjúban az AI megértésének jelentőségéről is beszél, továbbá kiderül, hogy programozóként, miért fontos neki a vizualitás, és plasztikus képet kapunk a mélytanulásról is. Varga Dánieltól hallunk a számára izgalmas geometriai problémákról és arról, hogy ez a terület miként kapcsolódik össze világhírű matematikus nagyapjával, aki egyébként a Rényi egykori igazgatója volt.
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March 11, 2025
The Team
The AI group at the institute brings together experts with backgrounds in both industry and academia. We place equal emphasis on theoretical foundations, thorough experimentation, and practical applications. Our close collaboration ensures a continuous exchange of knowledge between scientific research and applied projects.
All Theory Applications Former members
Balázs Szegedy
Mathematical Theory
Attila Börcs, PhD
NLP, Modeling, MLOps
Adrián Csiszárik
Representation Learning, Foundations
Győző Csóka
NLP, MLOps
Domonkos Czifra
NLP, Foundations
Botond Forrai
Modeling
Péter Kőrösi-Szabó
Modeling
Gábor Kovács
NLP, Modeling
Judit Laki, MD PhD
Healthcare
Márton Muntag
Time Series, NLP, Modeling
Dávid Terjék
Generalization, Mathematical Theory
Dániel Varga
Foundations, Computer aided proofs
Pál Zsámboki
Reinforcement Learning, Geometric Deep Learning
Zsolt Zombori
Formal Reasoning
Péter Ágoston
Combinatory, Geometry
Beatrix Mária Benkő
Representation Learning
Jakab Buda
NLP
Diego González Sánchez
Generalization, Mathematical Theory
Melinda F. Kiss
Representation Learning
Ákos Matszangosz
Topology, Foundations
Alex Olár
Foundations
Gergely Papp
Modeling
Open Positions
The Rényi AI group is actively recruiting both theorists and practitioners.
Machine Learning Engineer
Announcement: December 1, 2023
Deadline: rolling
applications
Rényi Institute is seeking Machine Learning Engineers to join our AI Research & Development team. Preferred Qualifications: • MLOps experience (especially in cloud environments) • Industry experience working on ML solutions
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Research Scientist
Announcement: December 1, 2023
Deadline: rolling
theory, applications
Rényi Institute is seeking Research Scientists to join our AI Research & Development team. You will have the privilege to work at a renowned academic institute and do what you love: do research and publish in the field of machine learning / deep learning.
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All Positions
Rényi AI - Building bridges between mathematics and artificial intelligence.