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M. Takác

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.AI1
same name
  • M. Takác — 6 papers, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedExpert or not? assessing data quality in offline reinforcement learning

1 citations · 2 across the 2 of their papers we have counts for

collaborators

4 papers

cs.LG2025★ 1 cited

Expert or not? assessing data quality in offline reinforcement learning

Arip Asadulaev, Fakhri Karray, Martin Takac

Offline reinforcement learning (RL) learns exclusively from static datasets, without further interaction with the environment. In practice, such datasets vary widely in quality, of…

cs.LG2025

Y-Shaped Generative Flows

Arip Asadulaev, Semyon Semenov, Abduragim Shtanchaev +3

Modern continuous-time generative models typically induce \emph{V-shaped} flows: each sample travels independently along a nearly straight trajectory from the prior to the data. Al…

cs.LG2025

Uncovering the Spectral Bias in Diagonal State Space Models

Ruben Solozabal, Velibor Bojkovic, Hilal AlQuabeh +2

Current methods for initializing state space models (SSMs) parameters mainly rely on the \textit{HiPPO framework}, which is based on an online approximation of orthogonal polynomia…

cs.AI2025★ 1 cited

The AI Data Scientist

Farkhad Akimov, Munachiso Samuel Nwadike, Zangir Iklassov +1

Imagine decision-makers uploading data and, within minutes, receiving clear, actionable insights delivered straight to their fingertips. That is the promise of the AI Data Scientis…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.