Publication
] What am I searching for?. (2018).
CBMM-Memo-096.pdf (1.74 MB)
CBMM-Memo-096.pdf (1.74 MB) What is changing when: decoding visual information in movies from human intracranial recordings. NeuroImage 180, Part A, 147-159 (2018). Human neurophysiological responses during movies (2.78 MB)
Human neurophysiological responses during movies (2.78 MB) Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences. Cell 177, 1009 (2019). Author's last draft (20.26 MB)
Author's last draft (20.26 MB) Psychology of Learning and Motivation 70, (2019).
Beyond the feedforward sweep: feedback computations in the visual cortex. Annals of the New York Academy of Sciences 1464, 222 - 241 (2020).
Beyond the feedforward sweep: feedback computations in the visual cortex. Ann. N.Y. Acad. Sci. | Special Issue: The Year in Cognitive Neuroscience 1464, 222-241 (2020). gk7812.pdf (1.93 MB)
gk7812.pdf (1.93 MB) Can Deep Learning Recognize Subtle Human Activities?. CVPR 2020 (2020).
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)
gk7967.pdf (3.07 MB) Minimal videos: Trade-off between spatial and temporal information in human and machine vision. Cognition (2020). doi:10.1016/j.cognition.2020.104263
A neural network trained for prediction mimics diverse features of biological neurons and perception. Nature Machine Intelligence 2, 210 - 219 (2020).
A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception. Nature Machine Learning (2020). 1805.10734.pdf (9.59 MB)
1805.10734.pdf (9.59 MB) What can human minimal videos tell us about dynamic recognition models?. International Conference on Learning Representations (ICLR 2020) (2020). at <https://baicsworkshop.github.io/pdf/BAICS_1.pdf> Authors' final version (516.09 KB)
Authors' final version (516.09 KB) XDream: Finding preferred stimuli for visual neurons using generative networks and gradient-free optimization. PLOS Computational Biology 16, e1007973 (2020). gk7791.pdf (2.39 MB)
gk7791.pdf (2.39 MB) Biological and Computer Vision. (Cambridge University Press, 2021). doi:10.1017/9781108649995
Cognitive boundary signals in the human medial temporal lobe shape episodic memory representation. bioRxiv (2021).
Frivolous Units: Wider Networks Are Not Really That Wide. AAAI 2021 (2021). at <https://dblp.org/rec/conf/aaai/CasperBDGSVK21.html> 1912.04783.pdf (6.69 MB)
1912.04783.pdf (6.69 MB) Hypothesis-driven Online Video Stream Learning with Augmented Memory. arXiv (2021). doi:10.48550/arXiv.2104.02206 2104.02206.pdf (2.25 MB)
2104.02206.pdf (2.25 MB) Localized task-invariant emotional valence encoding revealed by intracranial recordingsAbstract. Social Cognitive and Affective Neuroscience (2021). doi:10.1093/scan/nsab134
Mesoscopic physiological interactions in the human brain reveal small-world properties. Cell Reports 36, 109585 (2021).
Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. NeurIPS 2021 (2021). at <https://nips.cc/Conferences/2021/Schedule?showEvent=28848> gk8091.pdf (2.47 MB)
gk8091.pdf (2.47 MB) When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. International Conference on Computer Vision (ICCV) (2021). doi:10.1109/iccv48922.2021.00032 Bomatter_When_Pigs_Fly_Contextual_Reasoning_in_Synthetic_and_Natural_Scenes_ICCV_2021_paper.pdf (3.24 MB)
Bomatter_When_Pigs_Fly_Contextual_Reasoning_in_Synthetic_and_Natural_Scenes_ICCV_2021_paper.pdf (3.24 MB) Do computational models of vision need shape-based representations? Evidence from an individual with intriguing visual perceptions. Cognitive Neuropsychology 1 - 3 (2022). doi:10.1080/02643294.2022.2041588