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Thomas Brox

22 papers hereh-index 13488 citations29 works total

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

author position
  • middle author7
  • last author14

Across the 21 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • cs.LG9
  • cs.RO4
same name
  • Thomas Brox — 4 papers
  • Thomas Brox — 4 papers, h 5
  • Thomas Brox — 3 papers, h 3
  • Thomas Brox — 3 papers, h 3
  • Thomas Brox — 2 papers, h 1
  • Thomas Brox — 1 paper, h 1

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

activity
20222026
most citedDITTO: Demonstration Imitation by Trajectory Transformation

14 citations · 32 across the 21 of their papers we have counts for

collaborators
Showing 2024 · cs.LGShow all

4 papers · 2 filters

cs.LG2024★ 1 cited

Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning

Soumajyoti Sarkar, Leonard Lausen, Volkan Cevher +3

Sparse Mixture of Expert (SMoE) models have emerged as a scalable alternative to dense models in language modeling. These models use conditionally activated feedforward subnetworks…

cs.LG2024

Concept Bottleneck Models Without Predefined Concepts

Simon Schrodi, Julian Schur, Max Argus +1

There has been considerable recent interest in interpretable concept-based models such as Concept Bottleneck Models (CBMs), which first predict human-interpretable concepts and the…

cs.LG2024

Constrained Reinforcement Learning with Smoothed Log Barrier Function

Baohe Zhang, Yuan Zhang, Lilli Frison +2

Reinforcement Learning (RL) has been widely applied to many control tasks and substantially improved the performances compared to conventional control methods in many domains where…

cs.LG2024★ 5 cited

Is Mamba Capable of In-Context Learning?

Riccardo Grazzi, Julien Siems, Simon Schrodi +2

State of the art foundation models such as GPT-4 perform surprisingly well at in-context learning (ICL), a variant of meta-learning concerning the learned ability to solve tasks du…

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