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  • 2022

    AaltoNLP at SemEval-2022 Task 11: Ensembling Task-adaptive Pretrained Transformers for Multilingual Complex NER

    Pietiläinen, A. & Ji, S., 2022, SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop. Emerson, G., Schluter, N., Stanovsky, G., Kumar, R., Palmer, A., Schneider, N., Singh, S. & Ratan, S. (eds.). Association for Computational Linguistics, p. 1477-1482 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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    1 Citation (Scopus)
    2 Downloads (Pure)
  • Clustering Nursing Sentences-Comparing Three Sentence Embedding Methods

    Moen, H., Suhonen, H., Salanterä, S., Salakoski, T. & Peltonen, L. M., 25 May 2022, Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022. Seroussi, B., Weber, P., Dhombres, F., Grouin, C., Liebe, J-D., Liebe, J-D., Liebe, J-D., Pelayo, S., Pinna, A., Rance, B., Rance, B., Sacchi, L., Ugon, A., Ugon, A., Benis, A. & Gallos, P. (eds.). IOS PRESS, p. 854-858 5 p. (Studies in Health Technology and Informatics; vol. 294).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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    15 Downloads (Pure)
  • Contextualized Graph Embeddings for Adverse Drug Event Detection

    Gao, Y., Ji, S., Zhang, T., Tiwari, P. & Marttinen, P., 2022, (Accepted/In press) Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). 16 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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    10 Downloads (Pure)
  • Deconfounded Representation Similarity for Comparison of Neural Networks

    Cui, T., Kumar, Y., Marttinen, P. & Kaski, S., 2022, (Accepted/In press) Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  • Detecting Simpson’s Paradox: A Machine Learning Perspective

    Sharma, R., Garayev, H., Kaushik, M., Peious, S. A., Tiwari, P. & Draheim, D., 2022, Database and Expert Systems Applications - 33rd International Conference, DEXA 2022, Proceedings. Strauss, C., Cuzzocrea, A., Kotsis, G., Khalil, I. & Tjoa, A. M. (eds.). p. 323-335 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13426 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  • MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare

    Ji, S., Zhang, T., Ansari, L., Fu, J., Tiwari, P. & Cambria, E., 2022, Proceedings of the Thirteenth Language Resources and Evaluation Conference. European Language Resources Association (ELRA), p. 7184–7190

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
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  • Why Not to Trust Big Data: Discussing Statistical Paradoxes

    Sharma, R., Kaushik, M., Peious, S. A., Shahin, M., Vidyarthi, A., Tiwari, P. & Draheim, D., 2022, Database Systems for Advanced Applications. DASFAA 2022 International Workshops - BDMS, BDQM, GDMA, IWBT, MAQTDS, and PMBD, Proceedings. Rage, U. K., Goyal, V. & Reddy, P. K. (eds.). p. 50-63 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13248 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  • 2021

    A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models

    Rissanen, S. & Marttinen, P., 2021, Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Neural Information Processing Systems Foundation, p. 4207-4217 11 p. (Advances in Neural Information Processing Systems; vol. 6).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
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    2 Citations (Scopus)
    15 Downloads (Pure)
  • Emotion Recognition from Multi-channel EEG Data through A Dual-pipeline Graph Attention Network

    Li, X., Li, J., Zhang, Y. & Tiwari, P., 2021, Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021. Huang, Y., Kurgan, L., Luo, F., Hu, X. T., Chen, Y., Dougherty, E., Kloczkowski, A. & Li, Y. (eds.). IEEE, p. 3642-3647 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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    94 Downloads (Pure)
  • Medical Code Assignment with Gated Convolution and Note-Code Interaction

    Ji, S., Pan, S. & Marttinen, P., 1 Aug 2021, Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics, p. 1034-1043 10 p. (Annual Meeting of the Association for Computational Linguistics).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
    1 Citation (Scopus)
  • MedSeq2Seq: A Medical Knowledge Enriched Sequence to Sequence Learning Model for COVID-19 Diagnosis

    Zhang, Y., Rong, L., Li, X., Tiwari, P., Zheng, Q. & Liang, H., 2021, Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021. Huang, Y., Kurgan, L., Luo, F., Hu, X. T., Chen, Y., Dougherty, E., Kloczkowski, A. & Li, Y. (eds.). IEEE, p. 3181-3184 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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    3 Citations (Scopus)
    16 Downloads (Pure)
  • Multi-Task Learning for Jointly Detecting Depression and Emotion

    Zhang, Y., Li, X., Rong, L. & Tiwari, P., 2021, Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021. Huang, Y., Kurgan, L., Luo, F., Hu, X. T., Chen, Y., Dougherty, E., Kloczkowski, A. & Li, Y. (eds.). IEEE, p. 3142-3149 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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    7 Citations (Scopus)
    27 Downloads (Pure)
  • Multitask Recalibrated Aggregation Network for Medical Code Prediction

    Sun, W., Ji, S., Cambria, E. & Marttinen, P., 2021, Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track - European Conference, ECML PKDD 2021, Proceedings. Dong, Y., Kourtellis, N., Hammer, B. & Lozano, J. A. (eds.). p. 367-383 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12978 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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    25 Downloads (Pure)
  • 2020

    Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation

    Järvenpää, M., Vehtari, A. & Marttinen, P., 2020, Conference on Uncertainty in Artificial Intelligence (UAI 2020). Vol. 124. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
  • Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text

    Ji, S., Cambria, E. & Marttinen, P., 2020, Proceedings of the 3rd Clinical Natural Language Processing Workshop. Association for Computational Linguistics, p. 73-78

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
  • Learning Global Pairwise Interactions with Bayesian Neural Networks

    Cui, T., Marttinen, P. & Kaski, S., 24 Aug 2020, ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings. De Giacomo, G., Catala, A., Dilkina, B., Milano, M., Barro, S., Bugarin, A. & Lang, J. (eds.). IOS PRESS, p. 1087-1094 8 p. ( Frontiers in Artificial Intelligence and Applications; vol. 325).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
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    5 Citations (Scopus)
    20 Downloads (Pure)
  • Predicting utilization of healthcare services from individual disease trajectories using RNNs with multi-headed attention

    Kumar, Y., Salo, H., Nieminen, T., Vepsäläinen, K., Kulathinal, S. & Marttinen, P., 2020, Machine Learning for Health (ML4H) at NeurIPS 2019. p. 93-111 (Conference on Neural Information Processing Systems).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access