Publications
=============

| [1] M. Abavisani, D. Danks, S. Plis. `"GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints" <https://openreview.net/pdf?id=B_pCIsX8KL_>`_ International Conference on Learning Representations (ICLR) 2023

| [2] K. Solovyeva, D. Danks, M. Abavisani, S. Plis. `"Causal Learning through Deliberate Undersampling" <https://openreview.net/pdf?id=vfUSpAFyEC>`_ Conference on Causal Learning and Reasoning (CLeaR) 2023

| [3] A. Hyttinen, S. Plis, M. Järvisalo, F. Eberhardt, D. Danks. `"A constraint optimization approach to causal discovery from subsampled time series data." <https://arxiv.org/pdf/1602.07970.pdf>`_ International Journal of Approximate Reasoning 2017

| [4] D. Danks, S. Plis. `"Amalgamating evidence of dynamics." <https://link.springer.com/article/10.1007/s11229-017-1568-8>`_ Synthese, pp.1-18. 2017

| [5] S. Plis, D. Danks, J. Yang.  `"Mesochronal Structure Learning" <https://www.daviddanks.org/s/MSL-UAI15-final.pdf>`_  Uncertainty in Artificial Intelligence 2015

| [6] S. Plis, D. Danks, C. Freeman, V. D. Calhoun. `"Rate-Agnostic (Causal) structure learning" <https://papers.nips.cc/paper_files/paper/2015/file/e0ab531ec312161511493b002f9be2ee-Paper.pdf>`_ in Neural Information Processing System (NIPS) 2015

| [7] D. Danks, S. Plis `"Learning Causal Structure from Undersampled Time Series." <https://static1.squarespace.com/static/5f6d0320212a261d8716949f/t/6213236f9307777705961e04/1645421424041/DanksPlis-Final.pdf>`_  In: NIPS  2013 workshop  on causality;  2013 Dec  9; Lake Tahoe, Nevada, USA