Jeffrey Mark Siskind

Purdue University West Lafayette — United States

Computer Science · Physical Sciences

28h-index5.8kcitations113works0.22yr avg
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Research Topics

Multimodal Machine Learning Applications(25), Human Pose and Action Recognition(18), Logic, programming, and type systems(16), Natural Language Processing Techniques(14), Advanced Image and Video Retrieval Techniques(14)

Publications113 total

Towards Effective Human-in-the-Loop Assistive AI Agents
2025
The Repeated-Stimulus Confound in Electroencephalography
arXiv (Cornell University)·2025Open Access
Towards Effective Human-in-the-Loop Assistive AI Agents
arXiv (Cornell University)·2025· 1 citedOpen Access
Automatic Differentiation: Inverse Accumulation Mode
arXiv (Cornell University)·2024Open Access
Learning Exemplar Representations in Single-Trial EEG Category Decoding
2024
Still an Ineffective Method With Supertrials/ERPs—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features”
IEEE Transactions on Pattern Analysis and Machine Intelligence·2023· 6 citedOpen Access
Visual form of ASL verb signs predicts non-signer judgment of transitivity
PLoS ONE·2022· 7 citedOpen Access
Confounds in the Data—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features”
IEEE Transactions on Pattern Analysis and Machine Intelligence·2021· 11 citedOpen Access
Talk the talk and walk the walk: Dialogue-driven navigation in unknown indoor environments
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)·2021· 3 cited
Object classification from randomized EEG trials
2021· 3 citedOpen Access
The Amazing Race TM: Robot Edition
arXiv (Cornell University)·2020· 1 citedOpen Access
The Perils and Pitfalls of Block Design for EEG Classification Experiments
IEEE Transactions on Pattern Analysis and Machine Intelligence·2020· 109 citedOpen Access
Perturbation confusion in forward automatic differentiation of higher-order functions
Journal of Functional Programming·2019· 17 citedOpen Access
Training on the test set? An analysis of Spampinato et al. [31]
arXiv (Cornell University)·2018· 16 citedOpen Access
Learning Goal-Conditioned Value Functions with one-step Path rewards rather than Goal-Rewards
2018
Floyd-Warshall Reinforcement Learning: Learning from Past Experiences to\n Reach New Goals
arXiv (Cornell University)·2018· 3 citedOpen Access
Floyd-Warshall Reinforcement Learning: Learning from Past Experiences to Reach New Goals
arXiv (Cornell University)·2018· 10 citedOpen Access
A Critical Investigation of Deep Reinforcement Learning for Navigation
arXiv (Cornell University)·2018· 22 citedOpen Access
Automatic Differentiationin Machine Learning: a Survey
2018· 2 cited
Divide-and-conquer checkpointing for arbitrary
\nprograms with no user annotation
MURAL - Maynooth University Research Archive Library (National University of Ireland, Maynooth)·2018· 18 cited
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Frequent Co-authors

Barak A. Pearlmutter(12), Song Wang(7), Andrei Barbu(7), N. Siddharth(7), Daniel Paul Barrett(4), Haonan Yu(4), Ronnie Β. Wilbur(4), Sven Dickinson(3), Hamad Ahmed(3), Hari Bharadwaj(3), Atılım Güneş Baydin(2), Alexey Radul(2), Yu Cao(2), Aaron Michaux(2), Jared Sigurd Johansen(2), Thomas Victor Ilyevsky(2), Richard Mann(2), Allan Jepson(2), David McAllester(2), Alan Fern(2)