Spike Detection and Sorting: Combining Algebraic Differentiations with ICA. - Zoran Tiganj; Mamadou Mboup (ICA, 2009)

Deflation technique for neural spike sorting in multi-channel recordings. - Zoran Tiganj; Mamadou Mboup (MLSP, 2011)

On the pertinence of a numerical transmission model for neural information. - Zoran Tiganj (2011)

Influence of extracellular oscillations on neural communication: a computational perspective. - Zoran Tiganj; Sylvain Chevallier; Éric Monacelli (Frontiers Comput. Neurosci., 2014)

Efficient Neural Computation in the Laplace Domain. - Marc W. Howard; Karthik H. Shankar; Zoran Tiganj (CoCo@NIPS, 2015)

Scale Invariant Value Computation for Reinforcement Learning in Continuous Time. - Zoran Tiganj; Karthik H. Shankar; Marc W. Howard (AAAI Spring Symposia, 2017)

Neural and computational arguments for memory as a compressed supported timeline. - Zoran Tiganj; Karthik H. Shankar; Marc W. Howard (CogSci, 2017)

Compressed Timeline of Recent Experience in Monkey Lateral Prefrontal Cortex. - Zoran Tiganj; Jason A. Cromer; Jefferson E. Roy; Earl K. Miller; Marc W. Howard (J. Cogn. Neurosci., 2018)

Towards a neural-level cognitive architecture: modeling behavior in working memory tasks with neurons. - Zoran Tiganj; Nathanael Cruzado; Marc W. Howard (CogSci, 2019)

Estimating Scale-Invariant Future in Continuous Time. - Zoran Tiganj; Samuel J. Gershman; Per B. Sederberg; Marc W. Howard (Neural Comput., 2019)

A computational model for simulating the future using a memory timeline. - Zoran Tiganj; Wei Tang; Marc W. Howard (CogSci, 2021)

DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales. - Brandon G. Jacques; Zoran Tiganj; Marc W. Howard; Per B. Sederberg (NeurIPS, 2021)

SITHCon: A neural network robust to variations in input scaling on the time dimension. - Brandon G. Jacques; Zoran Tiganj; Aakash Sarkar; Marc W. Howard; Per B. Sederberg (CoRR, 2021)

Comparing Impact of Time Lag and Item Lag in Relative Judgment of Recency. - Sahaj Singh Maini; Louis Francis Labuzienski; Saurabh Gulati; Zoran Tiganj (CogSci, 2022)

A deep convolutional neural network that is invariant to time rescaling. - Brandon G. Jacques; Zoran Tiganj; Aakash Sarkar; Marc W. Howard; Per B. Sederberg (ICML, 2022)

Representing Latent Dimensions Using Compressed Number Lines. - Sahaj Singh Maini; James Mochizuki-Freeman; Chirag Shankar Indi; Brandon G. Jacques; Per B. Sederberg; Marc W. Howard; Zoran Tiganj (IJCNN, 2023)

Characterizing neural activity in cognitively inspired RL agents during an evidence accumulation task. - James Mochizuki-Freeman; Sahaj Singh Maini; Zoran Tiganj (IJCNN, 2023)

Geometry of abstract learned knowledge in deep RL agents. - James Mochizuki-Freeman; Md Rysul Kabir; Mitesh Gulecha; Zoran Tiganj (NeurReps, 2023)

Curriculum Learning With Infant Egocentric Videos. - Saber Sheybani; Himanshu Hansaria; Justin Wood; Linda B. Smith; Zoran Tiganj (NeurIPS, 2023)

Deep Reinforcement Learning with Time-Scale Invariant Memory. - Md Rysul Kabir; James Mochizuki-Freeman; Zoran Tiganj (AAAI, 2025)

Emergence of Episodic Memory in Transformers: Characterizing Changes in Temporal Structure of Attention Scores During Training. - Deven Mahesh Mistry; Anooshka Bajaj; Yash Aggarwal; Sahaj Singh Maini; Zoran Tiganj (NAACL (Long Papers), 2025)

Self-supervised learning of scale-invariant neural representations of space and time. - Abolfazl Alipour; Thomas W. James; Joshua W. Brown; Zoran Tiganj (J. Comput. Neurosci., 2025)