Cees Snoek
17 papers · 2019–2025 · 7 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (34)
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Keyword Champion
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Keyword Collector
(67)
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Century Club · Bronze
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Unstoppable · Bronze
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Research topics
Machine Learning
(13)
Artificial Intelligence
(11)
Deep Learning
(10)
Learning Paradigms · Artificial Intelligence
(10)
Learning Types · Machine Learning
(8)
Models
(7)
Core Methods
(5)
Application Areas
(4)
Bayesian & Probabilistic · Machine Learning
(4)
Optimization & Theory
(4)
Architectures
(3)
Bayesian & Probabilistic · Artificial Intelligence
(3)
Learning Paradigms · Machine Learning
(3)
Core AI
(2)
Learning Types · Deep Learning
(2)
Keywords
variational inference
(6)
few-shot learning
(5)
domain generalization
(2)
kernel methods
(2)
multi-task learning
(2)
variational bayesian inference
(2)
random feature
(2)
flow matching
(2)
variational random feature
(2)
transfer learning
(2)
semantic memory
(2)
diffusion model
(2)
bayesian neural network
(2)
knowledge distillation
(1)
knowledge transfer
(1)
self-supervised learning
(1)
uncertainty quantification
(1)
continual learning
(1)
image editing
(1)
semantic segmentation
(1)
Papers
GeneralizeFormer: Layer-Adaptive Model Generation across Test-Time Distribution Shifts
WACV 2025
Flow Matching for Conditional Text Generation in a Few Sampling Steps
EACL 2024
Latent Space Editing in Transformer-Based Flow Matching
AAAI 2024
SelEx: Self-Expertise in Fine-Grained Generalized Category Discovery
ECCV 2024
SIGMA: Sinkhorn-Guided Masked Video Modeling
ECCV 2024
Learning Unseen Modality Interaction
NeurIPS 2023
Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery
NeurIPS 2023
ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion
NeurIPS 2023
Association Graph Learning for Multi-Task Classification with Category Shifts
NeurIPS 2022
Variational Model Perturbation for Source-Free Domain Adaptation
NeurIPS 2022
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
ICML 2021
Kernel Continual Learning
ICML 2021
Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation
ACL 2021
Variational Prototype Inference for Few-Shot Semantic Segmentation
WACV 2021
Learning to Learn Kernels with Variational Random Features
ICML 2020
Learning to Learn Variational Semantic Memory
NeurIPS 2020
Hyperspherical Prototype Networks
NeurIPS 2019