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Workshop
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Fri 13:00
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Improving Counterfactual Explanations for Time Series Classification Models in Healthcare Settings
Tina Han · Jette Henderson · Pedram Akbarian Saravi · Joydeep Ghosh
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Workshop
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Mixed-Memory RNNs for Learning Long-term Dependencies in Irregularly-sampled Time Series
Mathias Lechner · Ramin Hasani
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Workshop
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Sat 9:25
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Q&A Causal feature selection in time series data
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Affinity Workshop
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Shapelet Guided Counterfactual Explanation Generation for Black-Box Time Series Classifiers
Tina Han · Jette Henderson
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Workshop
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Causal Discovery in Time Series Data Using Causally Invariant Locally Linear Models
Alexander Mey
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Poster
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Tue 9:00
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C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting
Shane Bergsma · Tim Zeyl · Javad Rahimipour Anaraki · Lei Guo
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Workshop
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Fri 9:30
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Empirical Evaluation of Data Augmentations for Biobehavioral Time Series Data with Deep Learning
Huiyuan Yang · Han Yu · Akane Sano
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Workshop
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Fri 13:00
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Prediction-Constrained Markov Models for Medical Time Series with Missing Data and Few Labels
Preetish Rath · Gabe Hope · Kyle Heuton · Erik Sudderth · Michael Hughes
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Workshop
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Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions
Violeta-Teodora Trifunov · Maha Shadaydeh · Joachim Denzler
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Poster
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Thu 14:00
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On the difficulty of learning chaotic dynamics with RNNs
Jonas Mikhaeil · Zahra Monfared · Daniel Durstewitz
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Workshop
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A Balanced Design of Time Series Experiments
Tu Ni · Iavor Bojinov · Jinglong Zhao
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Workshop
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Fri 13:00
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SurviVAEl: Variational Autoencoders for Clustering Time Series
Stefan Groha · Alexander Gusev · Sebastian Schmon
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