J. Zico Kolter

DEQ-MPC : Deep Equilibrium Model Predictive Control CORL 2025 Computing Low-Entropy Couplings for Large-Support Distributions UAI 2024 Scaling Laws for Data Filtering-- Data Curation cannot be Compute Agnostic CVPR 2024 Understanding Hallucinations in Diffusion Models through Mode Interpolation NIPS 2024 Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line NIPS 2024 One-Step Diffusion Distillation through Score Implicit Matching NIPS 2024 Rethinking LLM Memorization through the Lens of Adversarial Compression NIPS 2024 Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models NIPS 2024 Diffusing Differentiable Representations NIPS 2024 Function Approximation for Solving Stackelberg Equilibrium in Large Perfect Information Games AAAI 2023 On the Importance of Exploration for Generalization in Reinforcement Learning NIPS 2023 Deep Equilibrium Based Neural Operators for Steady-State PDEs NIPS 2023 Permutation Equivariant Neural Functionals NIPS 2023 One-Step Diffusion Distillation via Deep Equilibrium Models NIPS 2023 Learning with Explanation Constraints NIPS 2023 Language Models are Weak Learners NIPS 2023 Neural Functional Transformers NIPS 2023 Provably Bounding Neural Network Preimages NIPS 2023 Losses over Labels: Weakly Supervised Learning via Direct Loss Construction AAAI 2023 Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift NIPS 2022 Learning Options via Compression NIPS 2022 Characterizing Datapoints via Second-Split Forgetting NIPS 2022 The Pitfalls of Regularization in Off-Policy TD Learning NIPS 2022 Deep Equilibrium Approaches to Diffusion Models NIPS 2022 Deep Equilibrium Optical Flow Estimation CVPR 2022 General Cutting Planes for Bound-Propagation-Based Neural Network Verification NIPS 2022 Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation NIPS 2022 Test Time Adaptation via Conjugate Pseudo-labels NIPS 2022 Path Independent Equilibrium Models Can Better Exploit Test-Time Computation NIPS 2022 Joint inference and input optimization in equilibrium networks NIPS 2021 Monte Carlo Tree Search With Iteratively Refining State Abstractions NIPS 2021 Robustness between the worst and average case NIPS 2021 Adversarially robust learning for security-constrained optimal power flow NIPS 2021 Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification NIPS 2021 Boosted CVaR Classification NIPS 2021 Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds NIPS 2021 $(\textrm{Implicit})^2$: Implicit Layers for Implicit Representations NIPS 2021 Community detection using fast low-cardinality semidefinite programming NIPS 2020 Differentiable learning of numerical rules in knowledge graphs ICLR 2020 Fast is better than free: Revisiting adversarial training ICLR 2020 Deep Archimedean Copulas NIPS 2020 Efficient semidefinite-programming-based inference for binary and multi-class MRFs NIPS 2020 Multiscale Deep Equilibrium Models NIPS 2020 Monotone operator equilibrium networks NIPS 2020 Denoised Smoothing: A Provable Defense for Pretrained Classifiers NIPS 2020 Deep Equilibrium Models NIPS 2019 Low-Rank Semidefinite Programming for the MAX2SAT Problem AAAI 2019 Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games AAAI 2019 Multimodal Transformer for Unaligned Multimodal Language Sequences ACL 2019 A Continuous-Time View of Early Stopping for Least Squares Regression AISTATS 2019 Trellis Networks for Sequence Modeling ICLR 2019 Adversarial Music: Real world Audio Adversary against Wake-word Detection System NIPS 2019 Differentiable Convex Optimization Layers NIPS 2019 Learning Stable Deep Dynamics Models NIPS 2019 Uniform convergence may be unable to explain generalization in deep learning NIPS 2019 Differentiable MPC for End-to-end Planning and Control NIPS 2018 End-to-End Differentiable Physics for Learning and Control NIPS 2018 What Game Are We Playing? End-to-end Learning in Normal and Extensive Form Games IJCAI 2018 Scaling provable adversarial defenses NIPS 2018 OptNet: Differentiable Optimization as a Layer in Neural Networks ICML 2017 Gradient descent GAN optimization is locally stable NIPS 2017 A Semismooth Newton Method for Fast, Generic Convex Programming ICML 2017 Task-based End-to-end Model Learning in Stochastic Optimization NIPS 2017 Input Convex Neural Networks ICML 2017 The Multiple Quantile Graphical Model NIPS 2016 Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation AISTATS 2012 Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts JMLR 2007 Learning to Detect and Classify Malicious Executables in the Wild JMLR 2006