| 2023 | Residual-based error bound for physics-informed neural networks. | Shuheng Liu, Xiyue Huang, Pavlos Protopapas |
| 2023 | BISCUIT: Causal Representation Learning from Binary Interactions. | Phillip Lippe, Sara Magliacane, Sindy Lwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves |
| 2023 | Nonconvex stochastic scaled gradient descent and generalized eigenvector problems. | Chris Junchi Li, Michael I. Jordan |
| 2023 | Gaussian Process Surrogate Models for Neural Networks. | Michael Y. Li, Erin Grant, Thomas L. Griffiths |
| 2023 | Memory Mechanism for Unsupervised Anomaly Detection. | Jiahao Li, Yiqiang Chen, Yunbing Xing |
| 2023 | Finding Invariant Predictors Efficiently via Causal Structure. | Kenneth Lee, Md. Musfiqur Rahman, Murat Kocaoglu |
| 2023 | When are post-hoc conceptual explanations identifiable? | Tobias Leemann, Michael Kirchhof, Yao Rong, Enkelejda Kasneci, Gjergji Kasneci |
| 2023 | Towards better certified segmentation via diffusion models. | Othmane Laousy, Alexandre Araujo, Guillaume Chassagnon, Marie-Pierre Revel, Siddharth Garg, Farshad Khorrami, Maria Vakalopoulou |
| 2023 | Variable importance matching for causal inference. | Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page |
| 2023 | Fixed-Budget Best-Arm Identification with Heterogeneous Reward Variances. | Anusha Lalitha, Kousha Kalantari, Yifei Ma, Anoop Deoras, Branislav Kveton |
| 2023 | Optimal Budget Allocation for Crowdsourcing Labels for Graphs. | Adithya Kulkarni, Mohna Chakraborty, Sihong Xie, Qi Li |
| 2023 | Differentially private synthetic data using KD-trees. | Eleonora Kreacic, Navid Nouri, Vamsi K. Potluru, Tucker Balch, Manuela Veloso |
| 2023 | Reward-machine-guided, self-paced reinforcement learning. | Cevahir Kprl, Ufuk Topcu |
| 2023 | Risk-aware curriculum generation for heavy-tailed task distributions. | Cevahir Kprl, Thiago D. Simo, Nils Jansen, Ufuk Topcu |
| 2023 | Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting. | Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu |
| 2023 | Universal Graph Contrastive Learning with a Novel Laplacian Perturbation. | Taewook Ko, Yoonhyuk Choi, Chong-Kwon Kim |
| 2023 | Causal effect estimation from observational and interventional data through matrix weighted linear estimators. | Klaus-Rudolf Kladny, Julius von Kgelgen, Bernhard Schlkopf, Michael Muehlebach |
| 2023 | On Identifiability of Conditional Causal Effects. | Yaroslav Kivva, Jalal Etesami, Negar Kiyavash |
| 2023 | Phase-shifted adversarial training. | Yeachan Kim, Seongyeon Kim, Ihyeok Seo, Bonggun Shin |
| 2023 | How to use dropout correctly on residual networks with batch normalization. | Bum Jun Kim, Hyeyeon Choi, Hyeonah Jang, Donggeon Lee, Sang Woo Kim |
| 2023 | Assessing the Impact of Context Inference Error and Partial Observability on RL Methods for Just-In-Time Adaptive Interventions. | Karine Karine, Predrag V. Klasnja, Susan A. Murphy, Benjamin M. Marlin |
| 2023 | Fed-LAMB: Layer-wise and Dimension-wise Locally Adaptive Federated Learning. | Belhal Karimi, Ping Li, Xiaoyun Li |
| 2023 | Heavy-tailed linear bandit with Huber regression. | Minhyun Kang, Gi-Soo Kim |
| 2023 | Causal Discovery with Hidden Confounders using the Algorithmic Markov Condition. | David Kaltenpoth, Jilles Vreeken |
| 2023 | Nystrm M-Hilbert-Schmidt independence criterion. | Florian Kalinke, Zoltn Szab |