Martin Trapp
16 papers · 2019–2025 · 8 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (22)
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Keyword Collector
(62)
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Trend Setter
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Century Club Β· Bronze
π₯
Unstoppable Β· Bronze
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Conference Pioneer
Top co-authors
Research topics
Machine Learning
(13)
Artificial Intelligence
(12)
Bayesian & Probabilistic Β· Artificial Intelligence
(10)
Deep Learning
(7)
Optimization & Theory
(7)
Core Methods
(6)
Bayesian & Probabilistic Β· Machine Learning
(5)
Models
(5)
Core AI
(4)
Application Areas
(2)
Architectures
(2)
Learning Types Β· Machine Learning
(2)
Mathematics & Optimization
(1)
Learning Paradigms
(1)
Learning Types Β· Deep Learning
(1)
Keywords
probabilistic circuit
(7)
sum-product network
(3)
density estimation
(3)
uncertainty quantification
(3)
gaussian process
(3)
probabilistic modeling
(2)
bayesian inference
(2)
generative model
(2)
probabilistic inference
(2)
approximate inference
(2)
posterior inference
(2)
structure learning
(2)
variational inference
(2)
energy efficiency
(1)
automatic differentiation
(1)
deep learning
(1)
gaussian approximation
(1)
epistemic uncertainty
(1)
singular value decomposition
(1)
multi-output regression
(1)
Papers
Approximate Bayesian Inference via Bitstring Representations
UAI 2025
Flatness Improves Backbone Generalisation in Few-Shot Classification
WACV 2025
Streamlining Prediction in Bayesian Deep Learning
ICLR 2025
Fixing Overconfidence in Dynamic Neural Networks
WACV 2024
On Hardware-efficient Inference in Probabilistic Circuits
UAI 2024
Subtractive Mixture Models via Squaring: Representation and Learning
ICLR 2024
Characteristic Circuits
NeurIPS 2023
A Hardware Perspective to Evaluating Probabilistic Circuits
PGM 2022
Uncertainty-Guided Source-Free Domain Adaptation
ECCV 2022
Leveraging probabilistic circuits for nonparametric multi-output regression
UAI 2021
Periodic Activation Functions Induce Stationarity
NeurIPS 2021
Deep Structured Mixtures of Gaussian Processes
AISTATS 2020
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
ICML 2020
Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations
PGM 2020
Bayesian Learning of Sum-Product Networks
NeurIPS 2019
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
UAI 2019