Michael Kirchhof
9 papers · 2021–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓
🌍
Conference Polyglot · Silver
🌉
Interdisciplinary Bridge · Bronze
🗺️
Taxonomy Completionist
(17)
🔥
Unstoppable · Bronze
❓
The Questioner
Venues
Top co-authors
Research topics
Keywords
uncertainty quantification
(4)
aleatoric uncertainty
(3)
zero-shot learning
(2)
interactive learning
(1)
transfer learning
(1)
independent component analysis
(1)
principal component analysis
(1)
bayesian inference
(1)
embedding space
(1)
belief propagation
(1)
epistemic uncertainty
(1)
multi-label classification
(1)
posterior distribution
(1)
rule learning
(1)
probabilistic model
(1)
diffusion model
(1)
latent variable
(1)
language model
(1)
pre-trained model
(1)
out-of-distribution detection
(1)
Papers
Position: Uncertainty Quantification Needs Reassessment for Large Language Model Agents
ICML 2025
Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results
ACL 2025
Shielded Diffusion: Generating Novel and Diverse Images using Sparse Repellency
ICML 2025
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks
NeurIPS 2024
Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs
ICML 2023
URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates
NeurIPS 2023
When are post-hoc conceptual explanations identifiable?
UAI 2023
A Non-Isotropic Probabilistic Take On Proxy-Based Deep Metric Learning
ECCV 2022
pRSL: Interpretable multi-label stacking by learning probabilistic rules
UAI 2021