Kording, Konrad

14 publications

ICLR 2026 Falcon: Fast Proximal Linearization of Normalized Cuts for Unsupervised Image Segmentation Xiao Zhang, Xiangyu Han, Xiwen Lai, Yao Sun, Pei Zhang, Xia Liu, Konrad Kording

NeurIPS 2025 A Scalable, Causal, and Energy Efficient Framework for Neural Decoding with Spiking Neural Networks Georgios Mentzelopoulos, Ioannis Asmanis, Konrad Kording, Eva L Dyer, Kostas Daniilidis, Flavia Vitale

NeurIPS 2025 Does Object Binding Naturally Emerge in Large Pretrained Vision Transformers? Yihao Li, Saeed Salehi, Lyle Ungar, Konrad Kording

ICLRW 2025 The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications Philippe Brouillard, Chandler Squires, Jonas Wahl, Konrad Kording, Karen Sachs, Alexandre Drouin, Dhanya Sridhar

TMLR 2023 Automated Detection of Causal Inference Opportunities: Regression Discontinuity Subgroup Discovery Tony Liu, Patrick Lawlor, Lyle Ungar, Konrad Kording, Rahul Ladhania

ICMLW 2023 Automated Detection of Interpretable Causal Inference Opportunities: Regression Discontinuity Subgroup Discovery Tony Liu, Patrick Lawlor, Lyle Ungar, Konrad Kording, Rahul Ladhania

ICMLW 2023 Deep Networks as Paths on the Manifold of Neural Representations Richard D Lange, Devin Kwok, Jordan Kyle Matelsky, Xinyue Wang, David Rolnick, Konrad Kording

ICLR 2023 How Gradient Estimator Variance and Bias Impact Learning in Neural Networks Arna Ghosh, Yuhan Helena Liu, Guillaume Lajoie, Konrad Kording, Blake Aaron Richards

TMLR 2023 Learning Domain-Specific Causal Discovery from Time Series Xinyue Wang, Konrad Kording

TMLR 2022 Clustering Units in Neural Networks: Upstream vs Downstream Information Richard D Lange, David Rolnick, Konrad Kording

CLeaR 2022 Data-Driven Exclusion Criteria for Instrumental Variable Studies Tony Liu, Patrick Lawlor, Lyle Ungar, Konrad Kording

ICML 2020 Reverse-Engineering Deep ReLU Networks David Rolnick, Konrad Kording

ICLR 2019 Measuring and Regularizing Networks in Function Space Ari Benjamin, David Rolnick, Konrad Kording

ECCV 2018 Accelerating Dynamic Programs via Nested Benders Decomposition with Application to Multi-Person Pose Estimation Shaofei Wang, Alexander Ihler, Konrad Kording, Julian Yarkony