Samuel Kaski
- Group Factor Analysis
2014/11/21 by Arto Klami, Klami, Arto, Seppo Virtanen +5 · 5 citations
Biochemistry, Genetics and Molecular Biology · #Gene expression and cancer classification #Bioinformatics and Genomic Networks #Gene Regulatory Network Analysis
- Rethinking pooling in graph neural networks
2020/10/22 by Diego Mesquita, Mesquita, Diego, Amauri H. Souza +3 · 6 citations
Computer Science · #Advanced Graph Neural Networks #Graph Theory and Algorithms #Multimodal Machine Learning Applications
- Prior knowledge elicitation: The past, present, and future
2021/12/01 by Petrus Mikkola, Mikkola, Petrus, Osvaldo A. Martin +21 · 8 citations
Computer Science · Mathematics · Decision Sciences · #Bayesian Modeling and Causal Inference #Statistical Methods and Bayesian Inference #Forecasting Techniques and Applications
- Fundamentals and Recent Developments in Approximate Bayesian Computation
2016/10/19 by Jarno Lintusaari, Michael U. Gutmann, Ritabrata Dutta +2 · 5 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Gaussian Processes and Bayesian Inference #Markov Chains and Monte Carlo Methods
- Learning Robust Statistics for Simulation-based Inference under Model Misspecification
2023/05/25 by Daolang Huang, Huang, Daolang, Ayush Bharti +7 · 7 citations
Computer Science · Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
- Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
2015/08/18 by Markus Heinonen, Heinonen, Markus, Henrik Mannerström +7 · 3 citations
Computer Science · Mathematics · #Gaussian Processes and Bayesian Inference #Advanced Multi-Objective Optimization Algorithms #Markov Chains and Monte Carlo Methods
- Differentially Private Bayesian Learning on Distributed Data
2017/03/03 by Mikko Heikkilä, Heikkilä, Mikko, Eemil Lagerspetz +9 · 4 citations
Computer Science · Decision Sciences · #Privacy-Preserving Technologies in Data #Distributed Sensor Networks and Detection Algorithms #Data Quality and Management
- Amortized Probabilistic Conditioning for Optimization, Simulation and Inference
2024/10/20 by Paul E. Chang, Nasrulloh Loka, Chang, Paul E. +9 · 1 voice · 8 citations
Computer Science · Engineering · Mathematics · #Embedded Systems Design Techniques #Manufacturing Process and Optimization #Parallel Computing and Optimization Techniques #cs.LG #stat.ML
- Amortized Bayesian Experimental Design for Decision-Making
2024/11/04 by Daolang Huang, Yujia Guo, Huang, Daolang +5 · 2 voices · 4 citations
Decision Sciences · #Optimal Experimental Design Methods
- Federated Stochastic Gradient Langevin Dynamics
2020/04/23 by Khaoula El Mekkaoui, Mekkaoui, Khaoula El, Diego Mesquita +5 · 2 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Stochastic Gradient Optimization Techniques
- Deconfounded Representation Similarity for Comparison of Neural Networks
2022/01/31 by Tianyu Cui, Cui, Tianyu, Yogesh Kumar +5 · 2 citations
Computer Science · Materials Science · #Domain Adaptation and Few-Shot Learning #Topic Modeling #Machine Learning in Materials Science
- Tackling covariate shift with node-based Bayesian neural networks
2022/06/06 by Trung Trinh, Markus Heinonen, Trinh, Trung +5 · 2 citations
Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Machine Learning and Data Classification
- Approximate Bayesian Computation with Domain Expert in the Loop
2022/01/28 by Ayush Bharti, Louis Filstroff, Bharti, Ayush +3 · 2 citations
Computer Science · Mathematics · #Algorithms and Data Compression #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
- Variational zero-inflated Gaussian processes with sparse kernels
2018/03/13 by Pashupati Hegde, Hegde, Pashupati, Markus Heinonen +3 · 1 citation
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Statistical Mechanics and Entropy #Target Tracking and Data Fusion in Sensor Networks
- Machine Teaching of Active Sequential Learners
2018/09/08 by Tomi Peltola, Peltola, Tomi, Mustafa Mert Çelikok +5 · 1 voice
Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.AI #cs.HC #cs.LG #stat.ML
- Noise-Aware Statistical Inference with Differentially Private Synthetic Data
2022/05/28 by Ossi Räisä, Räisä, Ossi, Joonas Jälkö +5 · 1 citation
Computer Science · Engineering · Decision Sciences · #Privacy-Preserving Technologies in Data #Traffic Prediction and Management Techniques #Data Quality and Management
- Bayesian Optimization Augmented with Actively Elicited Expert Knowledge
2022/08/18 by Daolang Huang, Louis Filstroff, Huang, Daolang +7 · 1 citation
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Practical Equivariances via Relational Conditional Neural Processes
2023/06/19 by Daolang Huang, Manuel Haußmann, Huang, Daolang +13 · 1 citation
Computer Science · #Neural Networks and Applications #Explainable Artificial Intelligence (XAI) #Adversarial Robustness in Machine Learning
- Improving robustness to corruptions with multiplicative weight perturbations
2024/06/24 by Trung Trinh, Markus Heinonen, Trinh, Trung +5 · 1 citation
Social Sciences · #Corruption and Economic Development
- ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
2025/06/08 by Daolang Huang, Huang, Daolang, Ayush Bharti +6 · 2 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
- Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization
2025/02/03 by Minttu Alakuijala, Ya Gao, Alakuijala, Minttu +11 · 1 citation
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics
- Open Ad Hoc Teamwork with Cooperative Game Theory
2024/02/23 by Jianhong Wang, Yang Li, Wang, Jianhong +7 · 1 citation
Computer Science · #Distributed systems and fault tolerance #FOS: Computer and information sciences #Machine Learning (cs.LG) #Mobile Crowdsensing and Crowdsourcing #Multi-Agent Systems and Negotiation #Multiagent Systems (cs.MA)
- Decafs: Disentangled Conditional adversarial Flows
2026/07/21 by Anirudh jain, Sakshi Varshney, Samuel Kaski +1
#cs.LG