DSP group members will be traveling en masse to New Orleans in May 2019 to present four regular papers at the International Conference on Learning Representations

• R. Balestriero and R. G. Baraniuk, “Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference”
• J. Wang, R. Balestriero, and R. G. Baraniuk, “A Max-Affine Perspective of Recurrent Neural Networks”
• A. Mousavi, G. Dasarathy, and R. G. Baraniuk, “A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery”
• J. J. Michalenko, A. Shah, A. Verma, R. G. Baraniuk, S. Chaudhuri, and A. B. Patel, “Representing Formal Languages: A Comparison between Finite Automata and Recurrent Neural Networks”