Learning multiscale convolutional dictionaries for image reconstruction
Tianlin Liu, Anadi Chaman, David Belius, and Ivan Dokmanić
IEEE Transactions on Computational Imaging, 2022
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Sparsity-constrained optimal transport
Tianlin Liu, Joan Puigcerver, Mathieu Blondel
International Conference on Learning Representations (ICLR) 2023
Spotlight presentation
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Universal approximation under constraints is possible with transformers
Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, and Ivan Dokmanić
International Conference on Learning Representations (ICLR) 2022
Spotlight presentation

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Finding trainable sparse networks through neural tangent transfer
Tianlin Liu and Friedemann Zenke
International Conference on Machine Learning (ICML) 2020
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Causally denoise word embeddings using half-sibling regression
Zekun Yang*, Tianlin Liu* (*Equal contribution)
AAAI Conference on Artificial Intelligence 2020
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Continual learning for sentence representations using conceptors
Tianlin Liu, Lyle Ungar and João Sedoc
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT) 2019
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Reservoir transfer on analog neuromorphic hardware
Xu He, Tianlin Liu, Fatemeh Hadaeghi, and Herbert Jaeger
International IEEE EMBS Conference on Neural Engineering (NER) 2019.
Best paper finalist award (3rd place out of 467 accepted papers)
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Unsupervised post-processing of word vectors via conceptor negation
Tianlin Liu, Lyle Ungar, and João Sedoc
AAAI Conference on Artificial Intelligence 2019
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Fast binary compressive sensing via smoothed l0 gradient descent
Tianlin Liu and Dae Gwan Lee
International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa) 2018
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Correcting the common discourse bias in linear representation of sentences using conceptors
Tianlin Liu, João Sedoc, and Lyle Ungar
Biocreative/OHNLP workshop at ACM-BCB 2018
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Predicting engagement breakdown in HRI using thin-slices of facial expressions
Tianlin Liu and Arvid Kappas
AAAI Workshop on Affective Content Analysis 2018
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Harnesing slow dynamics in neuromorphic computation
Master thesis, Department of EE and CS, Jacobs University Bremen, 2019.
Deans Prize for outstanding master’s theses.
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Discrete compressive sensing: null space properties and convex optimization methods
Bachelor thesis, Department of Mathematics, Jacobs University Bremen, 2016.

Prepreint & technical report

A consistent method for learning OOMs from asymptotically stationary time series data containing missing values
Tianlin Liu
Technical report 2018
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