John K. Kruschke - Related publications

Indiana University, Bloomington, Bloomington, IN, United States 
attention in learning, connectionist models, bayesian statistics
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26 most relevant papers in past 60 days:
Year Citation  Score
2022 Hoppe DB, Hendriks P, Ramscar M, van Rij J. An exploration of error-driven learning in simple two-layer networks from a discriminative learning perspective. Behavior Research Methods. PMID 35032022 DOI: 10.3758/s13428-021-01711-5   
2022 Abirami RS, Kumar GS. Comparative Study Based on Analysis of Coronavirus Disease (COVID-19) Detection and Prediction Using Machine Learning Models. Sn Computer Science. 3: 79. PMID 34841267 DOI: 10.1007/s42979-021-00965-2   
2022 Liakoni V, Lehmann MP, Modirshanechi A, Brea J, Lutti A, Gerstner W, Preuschoff K. Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making. Neuroimage. 246: 118780. PMID 34875383 DOI: 10.1016/j.neuroimage.2021.118780   
2022 Nakawake Y, Kobayashi Y. Negative observational learning might play a limited role in the cultural evolution of technology. Scientific Reports. 12: 970. PMID 35046491 DOI: 10.1038/s41598-022-05031-2   
2022 Langdon A, Botvinick M, Nakahara H, Tanaka K, Matsumoto M, Kanai R. Meta-learning, social cognition and consciousness in brains and machines. Neural Networks : the Official Journal of the International Neural Network Society. 145: 80-89. PMID 34735893 DOI: 10.1016/j.neunet.2021.10.004   
2022 Wu Y, Zhao R, Zhu J, Chen F, Xu M, Li G, Song S, Deng L, Wang G, Zheng H, Ma S, Pei J, Zhang Y, Zhao M, Shi L. Brain-inspired global-local learning incorporated with neuromorphic computing. Nature Communications. 13: 65. PMID 35013198 DOI: 10.1038/s41467-021-27653-2   
2022 Andaur Navarro CL, Damen JAA, Takada T, Nijman SWJ, Dhiman P, Ma J, Collins GS, Bajpai R, Riley RD, Moons KGM, Hooft L. Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review. Bmc Medical Research Methodology. 22: 12. PMID 35026997 DOI: 10.1186/s12874-021-01469-6   
2022 Nicora G, Rios M, Abu-Hanna A, Bellazzi R. Evaluating Pointwise Reliability of Machine Learning prediction. Journal of Biomedical Informatics. 103996. PMID 35041981 DOI: 10.1016/j.jbi.2022.103996   
2022 Newton MAH, Mataeimoghadam F, Zaman R, Sattar A. Secondary structure specific simpler prediction models for protein backbone angles. Bmc Bioinformatics. 23: 6. PMID 34983370 DOI: 10.1186/s12859-021-04525-6   
2022 Lin C, Wang L, Shi L. AAPred-CNN: accurate predictor based on deep convolution neural network for identification of anti-angiogenic peptides. Methods (San Diego, Calif.). PMID 35031486 DOI: 10.1016/j.ymeth.2022.01.004   
2022 Jin MC, Rodrigues AJ, Jensen M, Veeravagu A. A Discussion of Machine Learning Approaches for Clinical Prediction Modeling. Acta Neurochirurgica. Supplement. 134: 65-73. PMID 34862529 DOI: 10.1007/978-3-030-85292-4_9   
2022 Roark CL, Plaut DC, Holt LL. A neural network model of the effect of prior experience with regularities on subsequent category learning. Cognition. 222: 104997. PMID 35007885 DOI: 10.1016/j.cognition.2021.104997   
2022 Gao Y, Gong M, Xie Y, Qin AK, Pan K, Ong YS. Multiparty Dual Learning. Ieee Transactions On Cybernetics. PMID 35044926 DOI: 10.1109/TCYB.2021.3139076   
2022 Soni PN, Shi S, Sriram PR, Ng AY, Rajpurkar P. Contrastive learning of heart and lung sounds for label-efficient diagnosis. Patterns (New York, N.Y.). 3: 100400. PMID 35079716 DOI: 10.1016/j.patter.2021.100400   
2022 Deng HF, Sun MW, Wang Y, Zeng J, Yuan T, Li T, Li DH, Chen W, Zhou P, Wang Q, Jiang H. Evaluating machine learning models for sepsis prediction: A systematic review of methodologies. Iscience. 25: 103651. PMID 35028534 DOI: 10.1016/j.isci.2021.103651   
2022 Liu Z, Zhu Z, Zheng S, Liu Y, Zhou J, Zhao Y. Margin Preserving Self-paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation. Ieee Journal of Biomedical and Health Informatics. PMID 34990372 DOI: 10.1109/JBHI.2022.3140853   
2022 Liquin EG, Lombrozo T. Motivated to learn: An account of explanatory satisfaction. Cognitive Psychology. 132: 101453. PMID 34875484 DOI: 10.1016/j.cogpsych.2021.101453   
2022 Wang W, Zhao F, Liao S, Shao L. Attentive WaveBlock: Complementarity-enhanced Mutual Networks for Unsupervised Domain Adaptation in Person Re-identification and Beyond. Ieee Transactions On Image Processing : a Publication of the Ieee Signal Processing Society. PMID 35015641 DOI: 10.1109/TIP.2022.3140614   
2022 Zhang K, Song X, Zhang C, Yu S. Challenges and future directions of secure federated learning: a survey. Frontiers of Computer Science. 16: 165817. PMID 34909232 DOI: 10.1007/s11704-021-0598-z   
2022 Mavridis CN, Baras JS. Online Deterministic Annealing for Classification and Clustering. Ieee Transactions On Neural Networks and Learning Systems. PMID 34995199 DOI: 10.1109/TNNLS.2021.3138676   
2022 Heffner CC, Fuhrmeister P, Luthra S, Mechtenberg H, Saltzman D, Myers EB. Reliability and validity for perceptual flexibility in speech. Brain and Language. 226: 105070. PMID 35026449 DOI: 10.1016/j.bandl.2021.105070   
2022 Chen NC, Chang YT, Chang PC, Chen CS, Lai CS. Learning outcomes of structured perioperative teaching based on adult learning. Plos One. 17: e0262872. PMID 35073352 DOI: 10.1371/journal.pone.0262872   
2022 de Kleijn R, Sen D, Kachergis G. A Critical Period for Robust Curriculum-Based Deep Reinforcement Learning of Sequential Action in a Robot Arm. Topics in Cognitive Science. PMID 35005844 DOI: 10.1111/tops.12595   
2022 Tang ZM, Oouchida Y, Wang MX, Dou ZL, Izumi SI. Observing errors in a combination of error and correct models favors observational motor learning. Bmc Neuroscience. 23: 4. PMID 34983385 DOI: 10.1186/s12868-021-00685-6   
2022 Liu M, Zhang C, Bai H, Zhang R, Zhao Y. Cross-Part Learning for Fine-Grained Image Classification. Ieee Transactions On Image Processing : a Publication of the Ieee Signal Processing Society. 31: 748-758. PMID 34928798 DOI: 10.1109/TIP.2021.3135477   
2022 de Boer B, Kudina O. What is morally at stake when using algorithms to make medical diagnoses? Expanding the discussion beyond risks and harms. Theoretical Medicine and Bioethics. PMID 34978638 DOI: 10.1007/s11017-021-09553-0