Force estimation and slip detection/classification for grip control using a biomimetic tactile sensor. - Zhe Su; Karol Hausman; Yevgen Chebotar; Artem Molchanov; Gerald E. Loeb; Gaurav S. Sukhatme; Stefan Schaal (Humanoids, 2015)

Active drifters: Towards a practical multi-robot system for ocean monitoring. - Artem Molchanov; Andreas Breitenmoser; Gaurav S. Sukhatme (ICRA, 2015)

Contact localization on grasped objects using tactile sensing. - Artem Molchanov; Oliver Kroemer; Zhe Su; Gaurav S. Sukhatme (IROS, 2016)

Circling the Seas: Design of Lagrangian Drifters for Ocean Monitoring. - Supreeth Subbaraya; Andreas Breitenmoser; Artem Molchanov; Jörg Müller 004; Carl Oberg; David A. Caron; Gaurav S. Sukhatme (IEEE Robotics Autom. Mag., 2016)

Synthetically Trained Neural Networks for Learning Human-Readable Plans from Real-World Demonstrations. - Jonathan Tremblay; Thang To; Artem Molchanov; Stephen Tyree; Jan Kautz; Stan Birchfield (ICRA, 2018)

Region Growing Curriculum Generation for Reinforcement Learning. - Artem Molchanov; Karol Hausman; Stan Birchfield; Gaurav S. Sukhatme (CoRR, 2018)

Sim-to-(Multi)-Real: Transfer of Low-Level Robust Control Policies to Multiple Quadrotors. - Artem Molchanov; Tao Chen; Wolfgang Hönig; James A. Preiss; Nora Ayanian; Gaurav S. Sukhatme (IROS, 2019)

Meta-Learning via Learned Loss. - Yevgen Chebotar; Artem Molchanov; Sarah Bechtle; Ludovic Righetti; Franziska Meier; Gaurav S. Sukhatme (CoRR, 2019)

Generalized Inner Loop Meta-Learning. - Edward Grefenstette; Brandon Amos; Denis Yarats; Phu Mon Htut; Artem Molchanov; Franziska Meier; Douwe Kiela; Kyunghyun Cho; Soumith Chintala (CoRR, 2019)

Meta Learning via Learned Loss. - Sarah Bechtle; Artem Molchanov; Yevgen Chebotar; Edward Grefenstette; Ludovic Righetti; Gaurav S. Sukhatme; Franziska Meier (ICPR, 2020)

Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning. - Sumeet Batra; Zhehui Huang; Aleksei Petrenko; Tushar Kumar; Artem Molchanov; Gaurav S. Sukhatme (CoRL, 2021)

Brain Principles Programming. - Evgenii Vityaev 001; Anton Kolonin; Andrey Kurpatov; Artem Molchanov (AGI, 2022)

Cognitive Architecture for Decision-Making Based on Brain Principles Programming. - Anton Kolonin; Andrey Kurpatov; Artem Molchanov; Gennadiy Averyanov (BICA*AI, 2022)

PredictionNet: Real-Time Joint Probabilistic Traffic Prediction for Planning, Control, and Simulation. - Alexey Kamenev; Lirui Wang; Ollin Boer Bohan; Ishwar Kulkarni; Bilal Kartal; Artem Molchanov; Stan Birchfield; David Nistér; Nikolai Smolyanskiy (ICRA, 2022)

Brain Principles Programming. - Evgenii Vityaev 001; Anton Kolonin; Artem Molchanov (CoRR, 2022)

Cognitive Architecture for Decision-Making Based on Brain Principles Programming. - Anton Kolonin; Andrey Kurpatov; Artem Molchanov (CoRR, 2022)

Cognitive Architecture for Decision-Making Based on Brain Principles Programming (in Russian). - Anton Kolonin; Andrey Kurpatov; Artem Molchanov; Gennadiy Averyanov (CoRR, 2023)

QuadSwarm: A Modular Multi-Quadrotor Simulator for Deep Reinforcement Learning with Direct Thrust Control. - Zhehui Huang; Sumeet Batra; Tao Chen; Rahul Krupani; Tushar Kumar; Artem Molchanov; Aleksei Petrenko; James A. Preiss; Zhaojing Yang; Gaurav S. Sukhatme (CoRR, 2023)