Export 45 results:
Filters: Author is Andrei Barbu [Clear All Filters]
Compositional Networks Enable Systematic Generalization for Grounded Language Understanding. (2021).
Compositional RL Agents That Follow Language Commands in Temporal Logic. Frontiers in Robotics and AI 8, (2021).
Large-scale benchmarking of deep neural network models in mouse visual cortex reveals patterns similar to those observed in macaque visual cortex. Cosyne (2021).
Measuring Social Biases in Grounded Vision and Language Embeddings. NAACL (Annual Conference of the North American Chapter of the Association for Computational Linguistics) (2021).
Multi-resolution modeling of a discrete stochastic process identifies causes of cancer. International Conference on Learning Representations (2021). at <https://openreview.net/forum?id=KtH8W3S_RE>
Neural Regression, Representational Similarity, Model Zoology Neural Taskonomy at Scale in Rodent Visual Cortex. (2021).
Spoken ObjectNet: A Bias-Controlled Spoken Caption Dataset. Interspeech 2021 (2021). doi:10.21437/Interspeech.2021
On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation. Shared Visual Representations in Human and Machine Intelligence (SVRHM) Workshop at NeurIPS (2021). at <https://openreview.net/forum?id=Rpazl253IHb>
Deep compositional robotic planners that follow natural language commands . International Conference on Robotics and Automation (ICRA) (2020).
Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2020). doi:10.1109/IROS45743.2020.9341325
Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas. (2020).
Learning a Natural-language to LTL Executable Semantic Parser for Grounded Robotics. (Proceedings of Conference on Robot Learning (CoRL-2020), 2020). at <https://corlconf.github.io/paper_385/>
Learning a natural-language to LTL executable semantic parser for grounded robotics. (2020). doi:https://doi.org/10.48550/arXiv.2008.03277
PHASE: PHysically-grounded Abstract Social Eventsfor Machine Social Perception. Shared Visual Representations in Human and Machine Intelligence (SVRHM) workshop at NeurIPS 2020 (2020). at <https://openreview.net/forum?id=_bokm801zhx>
Deep Compositional Robotic Planners that Follow Natural Language Commands. Workshop on Visually Grounded Interaction and Language (ViGIL) at the Thirty-third Annual Conference on Neural Information Processing Systems (NeurIPS), (2019). at <https://vigilworkshop.github.io/>
Deep video-to-video transformations for accessibility with an application to photosensitivity. Pattern Recognition Letters (2019). doi:10.1016/j.patrec.2019.01.019