◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

M. Kandemir

37 papers hereh-index 192.8k citations78 works total

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

author position
  • first author2
  • middle author20
  • last author15

Across the 37 of 37 papers where every author was matched, so the position is known.

fields
  • cs.LG30
  • stat.ML4
  • cs.CV3
same name
  • M. Kandemir — 20 papers, h 69
  • M. Kandemir — 8 papers, h 12
  • M. Kandemir — 5 papers, h 9
  • M. Kandemir — 3 papers, h 6
  • M. Kandemir — 3 papers, h 1
  • M. Kandemir — 1 paper, h 4

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
20182026
most citedIn the Picture: Medical Imaging Datasets, Artifacts, and their Living Review

16 citations · 44 across the 29 of their papers we have counts for

collaborators
Showing 2024 · cs.LGShow all

4 papers · 2 filters

cs.LG2024

Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning

Abdullah Akgül, Manuel Haußmann, Melih Kandemir

Current approaches to model-based offline reinforcement learning often incorporate uncertainty-based reward penalization to address the distributional shift problem. These approach…

cs.LG2024★ 1 cited

Improving Actor-Critic Training with Steerable Action-Value Approximation Errors

Bahareh Tasdighi, Nicklas Werge, Yi-Shan Wu +1

Off-policy actor-critic algorithms have shown strong potential in deep reinforcement learning for continuous control tasks. Their success primarily comes from leveraging pessimisti…

cs.LG2024

Calibrating Bayesian UNet++ for Sub-Seasonal Forecasting

Busra Asan, Abdullah Akgül, Alper Unal +2

Seasonal forecasting is a crucial task when it comes to detecting the extreme heat and colds that occur due to climate change. Confidence in the predictions should be reliable sinc…

cs.LG2024

Deep Exploration with PAC-Bayes

Bahareh Tasdighi, Manuel Haussmann, Nicklas Werge +2

Reinforcement learning (RL) for continuous control under delayed rewards is an under-explored problem despite its significance in real-world applications. Many complex skills are b…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.