publications

My Google Scholar profile.

Conference

Finding trainable sparse networks through neural tangent transfer
Tianlin Liu and Friedemann Zenke
International Conference on Machine Learning (ICML) 2020
pdf code slides bibtex

Causally denoise word embeddings using half-sibling regression
Zekun Yang*, Tianlin Liu* (*Equal contribution)
AAAI Conference on Artificial Intelligence 2020
pdf code poster bibtex

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
pdf code poster bibtex

Reservoir transfer on analog neuromorphic hardware
Xu He, Tianlin Liu, Fatemeh Hadaeghi, and Herbert Jaeger
International IEEE EMBS Conference on Neural Engineering (NER) 2019. 3rd best paper award of 467 accepted papers.
pdf code poster bibtex

Unsupervised post-processing of word vectors via conceptor negation
Tianlin Liu, Lyle Ungar, and João Sedoc
AAAI Conference on Artificial Intelligence 2019
pdf code poster bibtex

Workshop

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
pdf code bibtex

Correcting the common biscourse bias in linear representation of sentences using conceptors
Tianlin Liu, João Sedoc, and Lyle Ungar
Biocreative/OHNLP workshop at ACM-BCB 2018
pdf bibtex

Predicting engagement breakdown in HRI using thin-slices of facial expressions
Tianlin Liu and Arvid Kappas
AAAI Workshop on Affective Content Analysis 2018
pdf code bibtex

Theses

Harnesing slow dynamics in neuromorphic computation
Master thesis, Department of EE and CS, Jacobs University Bremen, 2019. Deans Prize for outstanding Master theses.
pdf code bibtex

Discrete compressive sensing: null space properties and convex optimization methods
Bachelor thesis, Department of Mathematics, Jacobs University Bremen, 2016.
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Prepreint & technical report

Interpreting U-Nets via task-driven multiscale dictionary learning
Tianlin Liu, Anadi Chaman, David Belius, and Ivan Dokmanić
Preprint 2020
pdf code bibtex

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