Publication
Export 897 results:
CUDA-Optimized real-time rendering of a Foveated Visual System. Shared Visual Representations in Human and Machine Intelligence (SVRHM) workshop at NeurIPS 2020 (2020). at <https://arxiv.org/abs/2012.08655>
Foveated_Drone_SVRHM_2020.pdf (13.44 MB)
v1 (12/15/2020) (14.7 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Deep compositional robotic planners that follow natural language commands. (2020).
CBMM-Memo-124.pdf (1.03 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Deep compositional robotic planners that follow natural language commands . International Conference on Robotics and Automation (ICRA) (2020).
Do Neural Networks for Segmentation Understand Insideness?. (2020).
CBMM-Memo-105.pdf (4.63 MB)
CBMM Memo 105 v2 (July 2, 2020) (3.2 MB)
CBMM Memo 105 v3 (January 25, 2022) (8.33 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Dreaming with ARC. Learning Meets Combinatorial Algorithms workshop at NeurIPS 2020 (2020).
CBMM Memo 113.pdf (1019.64 KB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Efficient inverse graphics in biological face processing. Science Advances 6, eaax5979 (2020).
eaax5979.full_.pdf (3.22 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Emergence of Pragmatic Reasoning From Least-Effort Optimization . 13th International Conference on the Evolution of Language (EvoLang) (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).
CBMM-Memo-125.pdf (2.12 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Evidence that recurrent pathways between the prefrontal and inferior temporal cortex is critical during core object recognition . COSYNE (2020).
An Exit Strategy from the Covid-19 Lockdown based on Risk-sensitive Resource Allocation. (2020).
CBMM-Memo-106.pdf (431.13 KB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Explicit regularization and implicit bias in deep network classifiers trained with the square loss. arXiv (2020). at <https://arxiv.org/abs/2101.00072>
Fast Recurrent Processing via Ventrolateral Prefrontal Cortex Is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition. Neuron (2020). doi:10.1016/j.neuron.2020.09.035
PIIS0896627320307595.pdf (3.92 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
The fine structure of surprise in intuitive physics: when, why, and how much?. Proceedings of the 42th Annual Meeting of the Cognitive Science Society - Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020, virtual, July 29 - August 1, 2020 ( ) (2020). at <https://cogsci.mindmodeling.org/2020/papers/0761/index.html>
For interpolating kernel machines, the minimum norm ERM solution is the most stable. (2020).
CBMM_Memo_108.pdf (1015.14 KB)
Better bound (without inequalities!) (1.03 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Function approximation by deep networks. Communications on Pure & Applied Analysis 19, 4085 - 4095 (2020).
1534-0392_2020_8_4085.pdf (514.57 KB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Hierarchical neural network models that more closely match primary visual cortex tend to better explain higher level visual cortical responses . COSYNE (2020).
Hierarchical structure is employed by humans during visual motion perception. Proceedings of the National Academy of Sciences 117, 24581 - 24589 (2020).
Hierarchically Local Tasks and Deep Convolutional Networks. (2020).
CBMM_Memo_109.pdf (2.12 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Implicit dynamic regularization in deep networks. (2020).
v1.2 (2.29 MB)
v.59 Update on rank (2.43 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Incorporating intrinsic suppression in deep neural networks captures dynamics of adaptation in neurophysiology and perception. Science Advances 6, eabd4205 (2020).
gk7967.pdf (3.07 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Infants represent 'like-kin' affiliation . Budapest Conference on Cognitive Development (2020).