◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Mario Lučić

4 papers here

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

author position
  • first author1
  • middle author1
  • last author2

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

fields
  • cs.LG3
  • stat.ML1

identity via Semantic Scholar / OpenAlex

activity
20142019
most citedRecent Advances in Autoencoder-Based Representation Learning

358 citations · 483 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2019★ 8 cited

Semantic Bottleneck Scene Generation

Samaneh Azadi, Michael Tschannen, Eric Tzeng +3

Coupling the high-fidelity generation capabilities of label-conditional image synthesis methods with the flexibility of unconditional generative models, we propose a semantic bottl…

cs.LG2019★ 94 cited

High-Fidelity Image Generation With Fewer Labels

Mario Lucic, Michael Tschannen, Marvin Ritter +3

Deep generative models are becoming a cornerstone of modern machine learning. Recent work on conditional generative adversarial networks has shown that learning complex, high-dimen…

cs.LG2018★ 358 cited

Recent Advances in Autoencoder-Based Representation Learning

Michael Tschannen, Olivier Bachem, Mario Lucic

Learning useful representations with little or no supervision is a key challenge in artificial intelligence. We provide an in-depth review of recent advances in representation lear…

stat.ML2014★ 23 cited

Fast and Robust Least Squares Estimation in Corrupted Linear Models

Brian McWilliams, Gabriel Krummenacher, Mario Lucic +1

Subsampling methods have been recently proposed to speed up least squares estimation in large scale settings. However, these algorithms are typically not robust to outliers or corr…

◍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.