Lindgren, Erik

6 publications

ICML 2021 Composing Normalizing Flows for Inverse Problems Jay Whang, Erik Lindgren, Alex Dimakis

NeurIPS 2021 Efficient Training of Retrieval Models Using Negative Cache Erik Lindgren, Sashank Reddi, Ruiqi Guo, Sanjiv Kumar

ICML 2020 Accelerating Large-Scale Inference with Anisotropic Vector Quantization Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar

NeurIPSW 2020 Approximate Probabilistic Inference with Composed Flows Jay Whang, Erik Lindgren, Alex Dimakis

NeurIPS 2018 Experimental Design for Cost-Aware Learning of Causal Graphs Erik Lindgren, Murat Kocaoglu, Alexandros G Dimakis, Sriram Vishwanath

NeurIPS 2016 Leveraging Sparsity for Efficient Submodular Data Summarization Erik Lindgren, Shanshan Wu, Alexandros G Dimakis