← Authors

Risto Miikkulainen

16 papers · 2008–2024 · 6 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (25) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (6) πŸƒ Academic Marathon (16) πŸ† Grand Slam πŸ’Ž Century Club (16) πŸ—ƒοΈ Keyword Collector (60) πŸš€ Conference Pioneer πŸ”₯ Unstoppable (7)

Conferences

ICLR (4) NIPS (4) AAAI (3) ICML (2) JMLR (2) COLING (1)

Top co-authors

Elliot Meyerson (6) Xin Qiu (5) Garrett Bingham (2) Faustino Gomez (1) Babak Hodjat (1) Kenneth McMillan (1) Mohit Tiwari (1) Wenxi Wang (1) Nora Aguirre-Celis (1) Darren Sargent (1)

Keywords

evolutionary algorithm (3) neural network (3) neural network optimization (2) uncertainty quantification (2) activation function (2) variational inference (1) policy optimization (1) multi-task learning (1) graph matching (1) hyperparameter optimization (1) probabilistic modeling (1) knowledge distillation (1) policy learning (1) neural architecture search (1) deep learning (1) domain adaptation (1) graph representation (1) multitask learning (1) error detection (1) transfer learning (1)

Papers

Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space NIPS 2024
NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks ICLR 2024
Unlocking the Potential of Global Human Expertise NIPS 2024
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural Networks AAAI 2023
Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search ICML 2023
Efficient Activation Function Optimization through Surrogate Modeling NIPS 2023
Detecting Misclassification Errors in Neural Networks with a Gaussian Process Model AAAI 2022
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings ICLR 2021
Characterizing Dynamic Word Meaning Representations in the Brain COLING 2020
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel ICLR 2020
Enhancing Evolutionary Conversion Rate Optimization via Multi-Armed Bandit Algorithms AAAI 2019
Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains NIPS 2019
Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering ICLR 2018
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharingβ€”and Back ICML 2018
Using Symmetry and Evolutionary Search to Minimize Sorting Networks JMLR 2013
Accelerated Neural Evolution through Cooperatively Coevolved Synapses JMLR 2008