Pekka Marttinen
22 papers · 2016–2025 · 13 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (9) π Interdisciplinary Bridge π Conference Polyglot (13) π§ Keyword Pioneer π Cross-Pollinator (12)
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(46)
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Interdisciplinary Bridge
β‘
Prolific Year
(7)
ποΈ
Keyword Collector
(93)
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Trend Setter
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Unstoppable
(6)
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Century Club
(22)
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The Questioner
Conferences
NIPS (5)
EMNLP (3)
ACL (2)
EACL (2)
JMLR (2)
AISTATS (1)
COLING (1)
ECCV (1)
ICLR (1)
ICML (1)
IJCNLP (1)
MICCAI (1)
UAI (1)
Top co-authors
Keywords
large language model
(4)
uncertainty quantification
(3)
in-context learning
(2)
gaussian process
(2)
code generation
(2)
bayesian inference
(2)
model-based reinforcement learning
(2)
point process
(2)
world model
(2)
causal inference
(2)
bayesian learning
(1)
likelihood-free inference
(1)
causal effect estimation
(1)
variational inference
(1)
zero-shot learning
(1)
attention mechanism
(1)
time series
(1)
epistemic uncertainty
(1)
dirichlet process
(1)
compositional generalization
(1)
Papers
Identifying latent state transitions in non-linear dynamical systems
ICLR 2025
New Multimodal Similarity Measure for Image Registration via Modeling Local Functional Dependence with Linear Combination of Learned Basis Functions
MICCAI 2025
Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search
NIPS 2024
Generating Demonstrations for In-Context Compositional Generalization in Grounded Language Learning
EMNLP 2024
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities
NIPS 2024
In-Context Symbolic Regression: Leveraging Large Language Models for Function Discovery
ACL 2024
Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection
COLING 2024
Can docstring reformulation with an LLM improve code generation?
EACL 2024
Improving Medical Multi-modal Contrastive Learning with Expert Annotations
ECCV 2024
Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning
EACL 2023
Reader: Model-based language-instructed reinforcement learning
EMNLP 2023
Causal Modeling of Policy Interventions From Treatment-Outcome Sequences
ICML 2023
Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach
AISTATS 2023
Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions
NIPS 2023
Deconfounded Representation Similarity for Comparison of Neural Networks
NIPS 2022
A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models
NIPS 2021
Medical Code Assignment with Gated Convolution and Note-Code Interaction
ACL 2021
Medical Code Assignment with Gated Convolution and Note-Code Interaction
IJCNLP 2021
Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text
EMNLP 2020
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation
UAI 2020
ELFI: Engine for Likelihood-Free Inference
JMLR 2018
Multiple Output Regression with Latent Noise
JMLR 2016