Alexander Pashevich

13 papers A* 2A 2Journal 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	DeepRRTime: Robust Time-series Forecasting with a Regularized INR Basis. Trans. Mach. Learn. Res. Chandramouli Shama Sastry, Mahdi Gilany, Kry Yik-Chau Lui, Martin Magill, Alexander Pashevich
2021	A*	`conf`	Episodic Transformer for Vision-and-Language Navigation. ICCV Alexander Pashevich, Cordelia Schmid, Chen Sun
2021	J	`jnl`	Episodic Transformer for Vision-and-Language Navigation. CoRR Alexander Pashevich, Cordelia Schmid, Chen Sun
2021	—	`—`	Robots that can see: Learning visually guided behavior. (Des robots qui voient: apprentissage de comportements guidés par la vision). Alexander Pashevich
2020	A*	`conf`	Learning to combine primitive skills: A step towards versatile robotic manipulation §. ICRA Robin Strudel, Alexander Pashevich, Igor Kalevatykh, Ivan Laptev, Josef Sivic, Cordelia Schmid
2020	A	`conf`	Learning visual policies for building 3D shape categories. IROS Alexander Pashevich, Igor Kalevatykh, Ivan Laptev, Cordelia Schmid
2020	J	`jnl`	Learning visual policies for building 3D shape categories. CoRR Alexander Pashevich, Igor Kalevatykh, Ivan Laptev, Cordelia Schmid
2019	J	`jnl`	Combining learned skills and reinforcement learning for robotic manipulations. CoRR Robin Strudel, Alexander Pashevich, Igor Kalevatykh, Ivan Laptev, Josef Sivic, Cordelia Schmid
2019	A	`conf`	Learning to Augment Synthetic Images for Sim2Real Policy Transfer. IROS Alexander Pashevich, Robin Strudel, Igor Kalevatykh, Ivan Laptev, Cordelia Schmid
2019	J	`jnl`	Learning to Augment Synthetic Images for Sim2Real Policy Transfer. CoRR Alexander Pashevich, Robin Strudel, Igor Kalevatykh, Ivan Laptev, Cordelia Schmid
2018	J	`jnl`	Modulated Policy Hierarchies. CoRR Alexander Pashevich, Danijar Hafner, James Davidson, Rahul Sukthankar, Cordelia Schmid
2018	J	`jnl`	Plane-extraction from depth-data using a Gaussian mixture regression model. Pattern Recognit. Lett. Richard T. Marriott, Alexander Pashevich, Radu Horaud
2017	J	`jnl`	Plane-extraction from depth-data using a Gaussian mixture regression model. CoRR Richard T. Marriott, Alexander Pashevich, Radu Horaud