Improving Density Estimation by Incorporating Spatial Information. - Laura M. Smith; Matthew S. Keegan; Todd Wittman; George O. Mohler; Andrea L. Bertozzi (EURASIP J. Adv. Signal Process., 2010)

Using Stochastic Models to Predict User Response in Social Media. - Tad Hogg; Kristina Lerman; Laura M. Smith (SocialCom, 2013)

The Role of Social Media in the Discussion of Controversial Topics. - Laura M. Smith; Linhong Zhu; Kristina Lerman; Zornitsa Kozareva (SocialCom, 2013)

Stochastic Models Predict User Behavior in Social Media. - Tad Hogg; Kristina Lerman; Laura M. Smith (CoRR, 2013)

Spectral Clustering with Epidemic Diffusion - Laura M. Smith; Kristina Lerman; Cristina Garcia-Cardona; Allon G. Percus; Rumi Ghosh (CoRR, 2013)

Partitioning Networks with Node Attributes by Compressing Information Flow. - Laura M. Smith; Linhong Zhu; Kristina Lerman; Allon G. Percus (ACM Trans. Knowl. Discov. Data, 2016)

SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning. - Marvin Zhang; Sharad Vikram; Laura M. Smith; Pieter Abbeel; Matthew J. Johnson 002; Sergey Levine (CoRR, 2018)

SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning. - Marvin Zhang; Sharad Vikram; Laura M. Smith; Pieter Abbeel; Matthew J. Johnson 002; Sergey Levine (ICML, 2019)

AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos. - Laura M. Smith; Nikita Dhawan; Marvin Zhang; Pieter Abbeel; Sergey Levine (Robotics: Science and Systems, 2020)

PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training. - Kimin Lee; Laura M. Smith; Pieter Abbeel (ICML, 2021)

B-Pref: Benchmarking Preference-Based Reinforcement Learning. - Kimin Lee; Laura M. Smith; Anca D. Dragan; Pieter Abbeel (NeurIPS Datasets and Benchmarks, 2021)

Offline Meta-Reinforcement Learning with Online Self-Supervision. - Vitchyr H. Pong; Ashvin Nair; Laura M. Smith; Catherine Huang; Sergey Levine (ICML, 2022)

Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World. - Laura M. Smith; J. Chase Kew; Xue Bin Peng; Sehoon Ha; Jie Tan 001; Sergey Levine (ICRA, 2022)

A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning. - Laura M. Smith; Ilya Kostrikov; Sergey Levine (CoRR, 2022)

RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning. - Kevin Zakka; Philipp Wu; Laura M. Smith; Nimrod Gileadi; Taylor Howell; Xue Bin Peng; Sumeet Singh; Yuval Tassa; Pete Florence; Andy Zeng 001; Pieter Abbeel (CoRL, 2023)

Efficient Online Reinforcement Learning with Offline Data. - Philip J. Ball; Laura M. Smith; Ilya Kostrikov; Sergey Levine (ICML, 2023)

Demonstrating A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning. - Ilya Kostrikov; Laura M. Smith; Sergey Levine (Robotics: Science and Systems, 2023)

Learning and Adapting Agile Locomotion Skills by Transferring Experience. - Laura M. Smith; J. Chase Kew; Tianyu Li; Linda Luu; Xue Bin Peng; Sehoon Ha; Jie Tan 001; Sergey Levine (Robotics: Science and Systems, 2023)

RoboPianist: A Benchmark for High-Dimensional Robot Control. - Kevin Zakka; Laura M. Smith; Nimrod Gileadi; Taylor A. Howell; Xue Bin Peng; Sumeet Singh; Yuval Tassa; Pete Florence; Andy Zeng 001; Pieter Abbeel (CoRR, 2023)

Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment. - Annie S. Chen; Govind Chada; Laura M. Smith; Archit Sharma; Zipeng Fu; Sergey Levine; Chelsea Finn (CoRR, 2023)

Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion. - Laura M. Smith; Yunhao Cao; Sergey Levine (ICRA, 2024)

HiLMa-Res: A General Hierarchical Framework via Residual RL for Combining Quadrupedal Locomotion and Manipulation. - Xiaoyu Huang; Qiayuan Liao; Yiming Ni; Zhongyu Li 003; Laura M. Smith; Sergey Levine; Xue Bin Peng; Koushil Sreenath (IROS, 2024)

D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning. - Rafael Rafailov; Kyle Beltran Hatch; Anikait Singh; Aviral Kumar; Laura M. Smith; Ilya Kostrikov; Philippe Hansen-Estruch; Victor Kolev; Philip J. Ball; Jiajun Wu 001; Sergey Levine; Chelsea Finn (RLJ, 2024)

Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models. - Annie S. Chen; Alec M. Lessing; Andy Tang; Govind Chada; Laura M. Smith; Sergey Levine; Chelsea Finn (CoRR, 2024)

Traversability-Aware Legged Navigation by Learning from Real-World Visual Data. - Hongbo Zhang; Zhongyu Li 003; Xuanqi Zeng; Laura M. Smith; Kyle Stachowicz; Dhruv Shah; Linzhu Yue; Zhitao Song; Weipeng Xia; Sergey Levine; Koushil Sreenath; Yun-hui Liu (CoRR, 2024)

STEER: Flexible Robotic Manipulation via Dense Language Grounding. - Laura M. Smith; Alex Irpan; Montserrat Gonzalez Arenas; Sean Kirmani; Dmitry Kalashnikov; Dhruv Shah; Ted Xiao (CoRR, 2024)

Language Guided Skill Discovery. - Seungeun Rho; Laura M. Smith; Tianyu Li; Sergey Levine; Xue Bin Peng; Sehoon Ha (ICLR, 2025)

π0.5: a Vision-Language-Action Model with Open-World Generalization. - Physical Intelligence; Kevin Black; Noah Brown; James Darpinian; Karan Dhabalia; Danny Driess; Adnan Esmail; Michael Equi; Chelsea Finn; Niccolo Fusai; Manuel Y. Galliker; Dibya Ghosh; et al. (CoRR, 2025)