default search action
Pekka Marttinen
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j34]Shaoxiong Ji, Xiaobo Li, Wei Sun, Hang Dong, Ara Taalas, Yijia Zhang, Honghan Wu, Esa Pitkänen, Pekka Marttinen:
A Unified Review of Deep Learning for Automated Medical Coding. ACM Comput. Surv. 56(12): 306:1-306:41 (2024) - [j33]Yogesh Kumar, Alexander Ilin, Henri Salo, Sangita Kulathinal, Maarit K. Leinonen, Pekka Marttinen:
Self-Supervised Forecasting in Electronic Health Records With Attention-Free Models. IEEE Trans. Artif. Intell. 5(8): 3926-3938 (2024) - [c24]Matteo Merler, Katsiaryna Haitsiukevich, Nicola Dainese, Pekka Marttinen:
In-Context Symbolic Regression: Leveraging Large Language Models for Function Discovery. ACL (Student Research Workshop) 2024: 589-606 - [c23]Ya Gao, Shaoxiong Ji, Pekka Marttinen:
Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection. LREC/COLING 2024: 9787-9798 - [c22]Nicola Dainese, Alexander Ilin, Pekka Marttinen:
Can docstring reformulation with an LLM improve code generation? EACL (Student Research Workshop) 2024: 296-312 - [c21]Sam Spilsbury, Pekka Marttinen, Alexander Ilin:
Generating Demonstrations for In-Context Compositional Generalization in Grounded Language Learning. EMNLP 2024: 15960-15991 - [c20]Chen He, Vishnu Raj, Hans Moen, Tommi Gröhn, Chen Wang, Laura-Maria Peltonen, Saila Koivusalo, Pekka Marttinen, Giulio Jacucci:
VMS: Interactive Visualization to Support the Sensemaking and Selection of Predictive Models. IUI 2024: 229-244 - [c19]Katsiaryna Haitsiukevich, Onur Poyraz, Pekka Marttinen, Alexander Ilin:
Diffusion Models as Probabilistic Neural Operators for Recovering Unobserved States of Dynamical Systems. MLSP 2024: 1-6 - [i41]Yogesh Kumar, Pekka Marttinen:
Improving Medical Multi-modal Contrastive Learning with Expert Annotations. CoRR abs/2403.10153 (2024) - [i40]Katsiaryna Haitsiukevich, Onur Poyraz, Pekka Marttinen, Alexander Ilin:
Diffusion models as probabilistic neural operators for recovering unobserved states of dynamical systems. CoRR abs/2405.07097 (2024) - [i39]Nicola Dainese, Matteo Merler, Minttu Alakuijala, Pekka Marttinen:
Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search. CoRR abs/2405.15383 (2024) - [i38]Minttu Alakuijala, Reginald McLean, Isaac Woungang, Nariman Farsad, Samuel Kaski, Pekka Marttinen, Kai Yuan:
Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics. CoRR abs/2405.19988 (2024) - [i37]Alexander Nikitin, Jannik Kossen, Yarin Gal, Pekka Marttinen:
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities. CoRR abs/2405.20003 (2024) - [i36]Çaglar Hizli, Çagatay Yildiz, Matthias Bethge, St John, Pekka Marttinen:
Identifying latent state transition in non-linear dynamical systems. CoRR abs/2406.03337 (2024) - [i35]Ya Gao, Hans Moen, Saila Koivusalo, Miika Koskinen, Pekka Marttinen:
Query-Guided Self-Supervised Summarization of Nursing Notes. CoRR abs/2407.04125 (2024) - 2023
- [j32]Sophie Wharrie, Zhiyu Yang, Vishnu Raj, Remo Monti, Rahul Gupta, Ying Wang, Alicia Martin, Luke J. O'Connor, Samuel Kaski, Pekka Marttinen, Pier Francesco Palamara, Christoph Lippert, Andrea Ganna:
HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes. Bioinform. 39(9) (2023) - [j31]Xiang Li, Yazhou Zhang, Prayag Tiwari, Dawei Song, Bin Hu, Meihong Yang, Zhigang Zhao, Neeraj Kumar, Pekka Marttinen:
EEG Based Emotion Recognition: A Tutorial and Review. ACM Comput. Surv. 55(4): 79:1-79:57 (2023) - [j30]Tommi Gröhn, Sammeli Liikkanen, Teppo Huttunen, Mika Mäkinen, Pasi Liljeberg, Pekka Marttinen:
Quantifying Movement Behavior of Chronic Low Back Pain Patients in Virtual Reality. ACM Trans. Comput. Heal. 4(2): 11:1-11:24 (2023) - [j29]Joel Honkamaa, Umair Khan, Sonja Koivukoski, Mira Valkonen, Leena Latonen, Pekka Ruusuvuori, Pekka Marttinen:
Deformation equivariant cross-modality image synthesis with paired non-aligned training data. Medical Image Anal. 90: 102940 (2023) - [j28]Saeed Karami, Farid Saberi-Movahed, Prayag Tiwari, Pekka Marttinen, Sahar Vahdati:
Unsupervised feature selection based on variance-covariance subspace distance. Neural Networks 166: 188-203 (2023) - [j27]Fanni Ojala, Mohamad R. Abdul Sater, Loren G. Miller, James A. McKinnell, Mary K. Hayden, Susan S. Huang, Yonatan H. Grad, Pekka Marttinen:
Bayesian modeling of the impact of antibiotic resistance on the efficiency of MRSA decolonization. PLoS Comput. Biol. 19(10) (2023) - [j26]Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multitask Balanced and Recalibrated Network for Medical Code Prediction. ACM Trans. Intell. Syst. Technol. 14(1): 17:1-17:20 (2023) - [c18]Vishnu Raj, Tianyu Cui, Markus Heinonen, Pekka Marttinen:
Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach. AISTATS 2023: 6741-6763 - [c17]Shaoxiong Ji, Pekka Marttinen:
Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning. EACL 2023: 589-598 - [c16]Nicola Dainese, Pekka Marttinen, Alexander Ilin:
Reader: Model-based language-instructed reinforcement learning. EMNLP 2023: 16583-16599 - [c15]Caglar Hizli, S. T. John, Anne Tuulikki Juuti, Tuure Tapani Saarinen, Kirsi Hannele Pietiläinen, Pekka Marttinen:
Causal Modeling of Policy Interventions From Treatment-Outcome Sequences. ICML 2023: 13050-13084 - [c14]Arina Odnoblyudova, Caglar Hizli, St John, Andrea Cognolato, Anne Juuti, Simo Särkkä, Kirsi Pietiläinen, Pekka Marttinen:
Nonparametric modeling of the composite effect of multiple nutrients on blood glucose dynamics. ML4H@NeurIPS 2023: 428-444 - [c13]Onur Poyraz, Pekka Marttinen:
Mixture of Coupled HMMs for Robust Modeling of Multivariate Healthcare Time Series. ML4H@NeurIPS 2023: 461-479 - [c12]Çaglar Hizli, St John, Anne Juuti, Tuure Saarinen, Kirsi Pietiläinen, Pekka Marttinen:
Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions. NeurIPS 2023 - [c11]Wei Sun, Shaoxiong Ji, Tuulia Denti, Hans Moen, Oleg Kerro, Antti Rannikko, Pekka Marttinen, Miika Koskinen:
Weak Supervision and Clustering-Based Sample Selection for Clinical Named Entity Recognition. ECML/PKDD (6) 2023: 444-459 - [i34]Shaoxiong Ji, Ya Gao, Pekka Marttinen:
Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection. CoRR abs/2301.10451 (2023) - [i33]Joel Honkamaa, Pekka Marttinen:
ASymReg: Robust symmetric image registration using anti-symmetric formulation and deformation inversion layers. CoRR abs/2303.10211 (2023) - [i32]Manish Bhatia, Balram Meena, Vipin Kumar Rathi, Prayag Tiwari, Amit Kumar Jaiswal, Shagaf M. Ansari, Ajay Kumar, Pekka Marttinen:
A Novel Deep Learning based Model for Erythrocytes Classification and Quantification in Sickle Cell Disease. CoRR abs/2305.01663 (2023) - [i31]Çaglar Hizli, S. T. John, Anne Juuti, Tuure Saarinen, Kirsi Pietiläinen, Pekka Marttinen:
Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions. CoRR abs/2306.09656 (2023) - [i30]Antti Pöllänen, Pekka Marttinen:
Identifiable causal inference with noisy treatment and no side information. CoRR abs/2306.10614 (2023) - [i29]Shaoxiong Ji, Wei Sun, Pekka Marttinen:
Content Reduction, Surprisal and Information Density Estimation for Long Documents. CoRR abs/2309.06009 (2023) - [i28]Mikko Kytö, Saila Koivusalo, Heli Tuomonen, Lisbeth Strömberg, Antti Ruonala, Pekka Marttinen, Seppo Heinonen, Giulio Jacucci:
Supporting Management of Gestational Diabetes with Comprehensive Self-Tracking: Mixed-Method Study of Wearable Sensors. CoRR abs/2309.07437 (2023) - [i27]Arina Odnoblyudova, Çaglar Hizli, St John, Andrea Cognolato, Anne Juuti, Simo Särkkä, Kirsi Pietiläinen, Pekka Marttinen:
Nonparametric modeling of the composite effect of multiple nutrients on blood glucose dynamics. CoRR abs/2311.03129 (2023) - [i26]Onur Poyraz, Pekka Marttinen:
Mixture of Coupled HMMs for Robust Modeling of Multivariate Healthcare Time Series. CoRR abs/2311.07867 (2023) - 2022
- [j25]Lang He, Mingyue Niu, Prayag Tiwari, Pekka Marttinen, Rui Su, Jiewei Jiang, Chenguang Guo, Hongyu Wang, Songtao Ding, Zhongmin Wang, Xiaoying Pan, Wei Dang:
Deep learning for depression recognition with audiovisual cues: A review. Inf. Fusion 80: 56-86 (2022) - [j24]Lang He, Prayag Tiwari, Rui Su, Xiuying Shi, Pekka Marttinen, Neeraj Kumar:
COVIDNet: An Automatic Architecture for COVID-19 Detection With Deep Learning From Chest X-Ray Images. IEEE Internet Things J. 9(13): 11376-11384 (2022) - [j23]Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu:
A Survey on Knowledge Graphs: Representation, Acquisition, and Applications. IEEE Trans. Neural Networks Learn. Syst. 33(2): 494-514 (2022) - [c10]Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski:
Deconfounded Representation Similarity for Comparison of Neural Networks. NeurIPS 2022 - [c9]Ya Gao, Shaoxiong Ji, Tongxuan Zhang, Prayag Tiwari, Pekka Marttinen:
Contextualized Graph Embeddings for Adverse Drug Event Detection. ECML/PKDD (2) 2022: 605-620 - [i25]Shaoxiong Ji, Wei Sun, Hang Dong, Honghan Wu, Pekka Marttinen:
A Unified Review of Deep Learning for Automated Medical Coding. CoRR abs/2201.02797 (2022) - [i24]Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski:
Deconfounded Representation Similarity for Comparison of Neural Networks. CoRR abs/2202.00095 (2022) - [i23]Xiang Li, Yazhou Zhang, Prayag Tiwari, Dawei Song, Bin Hu, Meihong Yang, Zhigang Zhao, Neeraj Kumar, Pekka Marttinen:
EEG based Emotion Recognition: A Tutorial and Review. CoRR abs/2203.11279 (2022) - [i22]Vishnu Raj, Tianyu Cui, Markus Heinonen, Pekka Marttinen:
Look beyond labels: Incorporating functional summary information in Bayesian neural networks. CoRR abs/2207.01234 (2022) - [i21]Joel Honkamaa, Umair Khan, Sonja Koivukoski, Leena Latonen, Pekka Ruusuvuori, Pekka Marttinen:
Deformation equivariant cross-modality image synthesis with paired non-aligned training data. CoRR abs/2208.12491 (2022) - [i20]Çaglar Hizli, S. T. John, Anne Juuti, Tuure Saarinen, Kirsi Pietiläinen, Pekka Marttinen:
Joint Non-parametric Point Process model for Treatments and Outcomes: Counterfactual Time-series Prediction Under Policy Interventions. CoRR abs/2209.04142 (2022) - 2021
- [j22]Shaoxiong Ji, Matti Hölttä, Pekka Marttinen:
Does the magic of BERT apply to medical code assignment? A quantitative study. Comput. Biol. Medicine 139: 104998 (2021) - [j21]Guangyi Zhang, Reza A. Ashrafi, Anne Juuti, Kirsi Pietiläinen, Pekka Marttinen:
Errors-in-Variables Modeling of Personalized Treatment-Response Trajectories. IEEE J. Biomed. Health Informatics 25(1): 201-208 (2021) - [c8]Shaoxiong Ji, Shirui Pan, Pekka Marttinen:
Medical Code Assignment with Gated Convolution and Note-Code Interaction. ACL/IJCNLP (Findings) 2021: 1034-1043 - [c7]Severi Rissanen, Pekka Marttinen:
A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models. NeurIPS 2021: 4207-4217 - [c6]Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multitask Recalibrated Aggregation Network for Medical Code Prediction. ECML/PKDD (4) 2021: 367-383 - [i19]Severi Rissanen, Pekka Marttinen:
A Critical Look At The Identifiability of Causal Effects with Deep Latent Variable Models. CoRR abs/2102.06648 (2021) - [i18]Shaoxiong Ji, Matti Hölttä, Pekka Marttinen:
Does the Magic of BERT Apply to Medical Code Assignment? A Quantitative Study. CoRR abs/2103.06511 (2021) - [i17]Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multitask Recalibrated Aggregation Network for Medical Code Prediction. CoRR abs/2104.00952 (2021) - [i16]Lang He, Mingyue Niu, Prayag Tiwari, Pekka Marttinen, Rui Su, Jiewei Jiang, Chenguang Guo, Hongyu Wang, Songtao Ding, Zhongmin Wang, Wei Dang, Xiaoying Pan:
Deep Learning for Depression Recognition with Audiovisual Cues: A Review. CoRR abs/2106.00610 (2021) - [i15]Yogesh Kumar, Alexander Ilin, Henri Salo, Sangita Kulathinal, Maarit K. Leinonen, Pekka Marttinen:
Medical SANSformers: Training self-supervised transformers without attention for Electronic Medical Records. CoRR abs/2108.13672 (2021) - [i14]Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multi-task Balanced and Recalibrated Network for Medical Code Prediction. CoRR abs/2109.02418 (2021) - [i13]Shaoxiong Ji, Pekka Marttinen:
Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning. CoRR abs/2109.03062 (2021) - 2020
- [c5]Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text. ClinicalNLP@EMNLP 2020: 73-78 - [c4]Tianyu Cui, Pekka Marttinen, Samuel Kaski:
Learning Global Pairwise Interactions with Bayesian Neural Networks. ECAI 2020: 1087-1094 - [c3]Marko Järvenpää, Aki Vehtari, Pekka Marttinen:
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation. UAI 2020: 779-788 - [i12]Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu:
A Survey on Knowledge Graphs: Representation, Acquisition and Applications. CoRR abs/2002.00388 (2020) - [i11]Tianyu Cui, Aki S. Havulinna, Pekka Marttinen, Samuel Kaski:
Informative Gaussian Scale Mixture Priors for Bayesian Neural Networks. CoRR abs/2002.10243 (2020) - [i10]Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text. CoRR abs/2009.14578 (2020) - [i9]Shaoxiong Ji, Shirui Pan, Pekka Marttinen:
Medical Code Assignment with Gated Convolution and Note-Code Interaction. CoRR abs/2010.06975 (2020)
2010 – 2019
- 2019
- [j20]Jussi Gillberg, Pekka Marttinen, Hiroshi Mamitsuka, Samuel Kaski:
Modelling G×E with historical weather information improves genomic prediction in new environments. Bioinform. 35(20): 4045-4052 (2019) - [j19]Marko Järvenpää, Mohamad R. Abdul Sater, Georgia K. Lagoudas, Paul C. Blainey, Loren G. Miller, James A. McKinnell, Susan S. Huang, Yonatan H. Grad, Pekka Marttinen:
A Bayesian model of acquisition and clearance of bacterial colonization incorporating within-host variation. PLoS Comput. Biol. 15(4) (2019) - [c2]Yogesh Kumar, Henri Salo, Tuomo Nieminen, Kristian Vepsalainen, Sangita Kulathinal, Pekka Marttinen:
Predicting utilization of healthcare services from individual disease trajectories using RNNs with multi-headed attention. ML4H@NeurIPS 2019: 93-111 - [i8]Tianyu Cui, Pekka Marttinen, Samuel Kaski:
Recovering Pairwise Interactions Using Neural Networks. CoRR abs/1901.08361 (2019) - [i7]Marko Järvenpää, Michael U. Gutmann, Aki Vehtari, Pekka Marttinen:
Parallel Gaussian process surrogate method to accelerate likelihood-free inference. CoRR abs/1905.01252 (2019) - [i6]Guangyi Zhang, Reza A. Ashrafi, Anne Juuti, Kirsi Pietiläinen, Pekka Marttinen:
Errors-in-variables Modeling of Personalized Treatment-Response Trajectories. CoRR abs/1906.03989 (2019) - [i5]Marko Järvenpää, Aki Vehtari, Pekka Marttinen:
Batch simulations and uncertainty quantification in Gaussian process surrogate-based approximate Bayesian computation. CoRR abs/1910.06121 (2019) - 2018
- [j18]Aleksi Sipola, Pekka Marttinen, Jukka Corander:
Bacmeta: simulator for genomic evolution in bacterial metapopulations. Bioinform. 34(13): 2308-2310 (2018) - [j17]Iiris Sundin, Tomi Peltola, Luana Micallef, Homayun Afrabandpey, Marta Soare, Muntasir Mamun Majumder, Pedram Daee, Chen He, Baris Serim, Aki S. Havulinna, Caroline Heckman, Giulio Jacucci, Pekka Marttinen, Samuel Kaski:
Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge. Bioinform. 34(13): i395-i403 (2018) - [j16]Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Pekka Marttinen, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski:
ELFI: Engine for Likelihood-Free Inference. J. Mach. Learn. Res. 19: 16:1-16:7 (2018) - [i4]Marko Järvenpää, Mohamad R. Abdul Sater, Georgia K. Lagoudas, Paul C. Blainey, Loren G. Miller, James A. McKinnell, Susan S. Huang, Yonatan H. Grad, Pekka Marttinen:
A Bayesian model of acquisition and clearance of bacterial colonization. CoRR abs/1811.10958 (2018) - 2017
- [j15]Matti Pirinen, Christian Benner, Pekka Marttinen, Marjo-Riitta Järvelin, Manuel A. Rivas, Samuli Ripatti:
biMM: efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements. Bioinform. 33(15): 2405-2407 (2017) - [j14]Pekka Marttinen, William P. Hanage:
Speciation trajectories in recombining bacterial species. PLoS Comput. Biol. 13(7) (2017) - [c1]Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski:
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. IUI 2017: 547-552 - [i3]Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder, Pedram Daee, Marta Soare, Homayun Afrabandpey, Caroline Heckman, Samuel Kaski, Pekka Marttinen:
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation. CoRR abs/1705.03290 (2017) - 2016
- [j13]Anna Cichonska, Juho Rousu, Pekka Marttinen, Antti J. Kangas, Pasi Soininen, Terho Lehtimäki, Olli T. Raitakari, Marjo-Riitta Järvelin, Veikko Salomaa, Mika Ala-Korpela, Samuli Ripatti, Matti Pirinen:
metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis. Bioinform. 32(13): 1981-1989 (2016) - [j12]Jussi Gillberg, Pekka Marttinen, Matti Pirinen, Antti J. Kangas, Pasi Soininen, Mehreen Ali, Aki S. Havulinna, Marjo-Riitta Järvelin, Mika Ala-Korpela, Samuel Kaski:
Multiple Output Regression with Latent Noise. J. Mach. Learn. Res. 17: 122:1-122:35 (2016) - [i2]Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski:
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. CoRR abs/1612.02487 (2016) - 2014
- [j11]Pekka Marttinen, Matti Pirinen, Antti-Pekka Sarin, Jussi Gillberg, Johannes Kettunen, Ida Surakka, Antti J. Kangas, Pasi Soininen, Paul F. O'Reilly, Marika Kaakinen, Mika Kähönen, Terho Lehtimäki, Mika Ala-Korpela, Olli T. Raitakari, Veikko Salomaa, Marjo-Riitta Järvelin, Samuli Ripatti, Samuel Kaski:
Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression. Bioinform. 30(14): 2026-2034 (2014) - 2013
- [i1]Jussi Gillberg, Pekka Marttinen, Matti Pirinen, Antti J. Kangas, Pasi Soininen, Marjo-Riitta Järvelin, Mika Ala-Korpela, Samuel Kaski:
Bayesian Information Sharing Between Noise And Regression Models Improves Prediction of Weak Effects. CoRR abs/1310.4362 (2013) - 2010
- [j10]Pekka Marttinen, Jukka Corander:
Efficient Bayesian approach for multilocus association mapping including gene-gene interactions. BMC Bioinform. 11: 443 (2010)
2000 – 2009
- 2009
- [j9]Pekka Marttinen, Samuel Myllykangas, Jukka Corander:
Bayesian clustering and feature selection for cancer tissue samples. BMC Bioinform. 10 (2009) - [j8]Petri Törönen, Pauli J. Ojala, Pekka Marttinen, Liisa Holm:
Robust extraction of functional signals from gene set analysis using a generalized threshold free scoring function. BMC Bioinform. 10: 307 (2009) - [j7]Pekka Marttinen, Jukka Corander:
Bayesian learning of graphical vector autoregressions with unequal lag-lengths. Mach. Learn. 75(2): 217-243 (2009) - [j6]Pekka Marttinen, Jing Tang, Bernard De Baets, Peter Dawyndt, Jukka Corander:
Bayesian Clustering of Fuzzy Feature Vectors Using a Quasi-Likelihood Approach. IEEE Trans. Pattern Anal. Mach. Intell. 31(1): 74-85 (2009) - 2008
- [j5]Jukka Corander, Pekka Marttinen, Jukka Sirén, Jing Tang:
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinform. 9 (2008) - [j4]Pekka Marttinen, Adam Baldwin, William P. Hanage, Chris Dowson, Eshwar Mahenthiralingam, Jukka Corander:
Bayesian modeling of recombination events in bacterial populations. BMC Bioinform. 9 (2008) - 2006
- [j3]Pekka Marttinen, Jukka Corander, Petri Törönen, Liisa Holm:
Bayesian search of functionally divergent protein subgroups and their function specific residues. Bioinform. 22(20): 2466-2474 (2006) - [j2]Jukka Corander, Pekka Marttinen:
Bayesian Model Learning Based on Predictive Entropy. J. Log. Lang. Inf. 15(1-2): 5-20 (2006) - 2004
- [j1]Jukka Corander, Patrik Waldmann, Pekka Marttinen, Mikko J. Sillanpää:
BAPS 2: enhanced possibilities for the analysis of genetic population structure. Bioinform. 20(15): 2363-2369 (2004)