A Note on Learning Vector Quantization. - Virginia R. de Sa; Dana H. Ballard (NIPS, 1992)

Learning Classification with Unlabeled Data. - Virginia R. de Sa (NIPS, 1993)

Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs. - Rich Caruana; Virginia R. de Sa (NIPS, 1996)

Using Helmholtz Machines to Analyze Multi-channel Neuronal Recordings. - Virginia R. de Sa; R. Christopher DeCharms; Michael Merzenich (NIPS, 1997)

Category Learning Through Multi-Modality Sensing. - Virginia R. de Sa; Dana H. Ballard (Neural Comput., 1998)

Model fitting as an aid to bridge balancing in neuronal recording. - Virginia R. de Sa; David J. C. MacKay (Neurocomputing, 2001)

Sensory Modality Segregation. - Virginia R. de Sa (NIPS, 2003)

Benefitting from the Variables that Variable Selection Discards. - Rich Caruana; Virginia R. de Sa (J. Mach. Learn. Res., 2003)

A temporal trace and SOM-based model of complex cell development. - Thomas J. Sullivan; Virginia R. de Sa (Neurocomputing, 2004)

Nonlinear reverse correlation with synthesized naturalistic noise. - Hsin-Hao Yu; Virginia R. de Sa (Neurocomputing, 2004)

A self-organizing map with homeostatic synaptic scaling. - Thomas J. Sullivan; Virginia R. de Sa (Neurocomputing, 2006)

A model of surround suppression through cortical feedback. - Thomas J. Sullivan; Virginia R. de Sa (Neural Networks, 2006)

Homeostatic synaptic scaling in self-organizing maps. - Thomas J. Sullivan; Virginia R. de Sa (Neural Networks, 2006)

Preprocessing and Meta-Classification for Brain-Computer Interfaces. - Paul S. Hammon; Virginia R. de Sa (IEEE Trans. Biomed. Eng., 2007)

Sleeping Our Way to Weight Normalization and Stable Learning. - Thomas J. Sullivan; Virginia R. de Sa (Neural Comput., 2008)

Predicting Reaching Targets from Human EEG. - Paul S. Hammon; Scott Makeig; Howard Poizner; Emanuel Todorov; Virginia R. de Sa (IEEE Signal Process. Mag., 2008)

Multi-view kernel construction. - Virginia R. de Sa; Patrick W. Gallagher; Joshua M. Lewis; Vicente L. Malave (Mach. Learn., 2010)

Coordinating Touch and Vision to Learn What Objects Look Like. - Walter A. Talbott; Ian R. Fasel; Javier Molina; Virginia R. de Sa; Javier R. Movellan (CogSci, 2011)

Human Cluster Evaluation and Formal Quality Measures: A Comparative Study. - Joshua M. Lewis; Margareta Ackerman; Virginia R. de Sa (CogSci, 2012)

A Behavioral Investigation of Dimensionality Reduction. - Joshua M. Lewis; Laurens van der Maaten; Virginia R. de Sa (CogSci, 2012)

Using Machine Learning for Exploratory Data Analysis. - Joshua M. Lewis; Virginia R. de Sa (CogSci, 2012)

Learning Cluster Analysis through Experience. - Joshua M. Lewis; Virginia R. de Sa (CogSci, 2012)

An interactive control strategy is more robust to non-optimal classification boundaries. - Virginia R. de Sa (ICMI, 2012)

Divvy: fast and intuitive exploratory data analysis. - Joshua M. Lewis; Virginia R. de Sa; Laurens van der Maaten (J. Mach. Learn. Res., 2013)

Single-trial identification of failed memory retrieval. - Eunho Noh; Matthew V. Mollison; Tim Curran; Virginia R. de Sa (ACSSC, 2014)

Discriminative dimensionality reduction for analyzing EEG data. - Eunho Noh; Virginia R. de Sa (CogSci, 2014)

Using single-trial EEG to predict and analyze subsequent memory. - Eunho Noh; Grit Herzmann; Tim Curran; Virginia R. de Sa (NeuroImage, 2014)

Deep Recurrent Convolutional Neural Networks for Classifying P300 BCI signals. - Ramesh Maddula; Joshua Stivers; Mahta Mousavi; Sriram Ravindran; Virginia de Sa (GBCIC, 2017)

Csp-NN: a Convolutional Neural Network Implementation of Common Spatial Patterns. - Daniel Maryanovsky; Mahta Mousavi; Nathanial Moreno; Virginia de Sa (GBCIC, 2017)

Towards Elaborated feedback for Training motor imagery brain Computer Interfaces. - Mahta Mousavi; Virginia de Sa (GBCIC, 2017)

Improving Information Transfer rate in Active BCIs. - Virginia de Sa (GBCIC, 2017)

Spelling in Parallel: towards a Rapid, spatially Independent BCI. - Joshua Stivers; Virginia de Sa (GBCIC, 2017)

Rethinking Skip-thought: A Neighborhood based Approach. - Shuai Tang; Hailin Jin; Chen Fang; Zhaowen Wang; Virginia R. de Sa (Rep4NLP@ACL, 2017)

Trimming and Improving Skip-thought Vectors. - Shuai Tang; Hailin Jin; Chen Fang; Zhaowen Wang; Virginia R. de Sa (CoRR, 2017)

Exploring Asymmetric Encoder-Decoder Structure for Context-based Sentence Representation Learning. - Shuai Tang; Hailin Jin; Chen Fang; Zhaowen Wang; Virginia R. de Sa (CoRR, 2017)

Adaptive CSP with subspace alignment for subject-to-subject transfer in motor imagery brain-computer interfaces. - Yiming Jin; Mahta Mousavi; Virginia R. de Sa (BCI, 2018)

Single-Trial EEG Predicts Memory Retrieval Using Leave-One-Subject-Out Classification. - Kueida Liao; Matthew V. Mollison; Tim Curran; Virginia R. de Sa (BIBM, 2018)

Automated Pain Assessment using Electrodermal Activity Data and Machine Learning. - Busra T. Susam; Murat Akçakaya; Hooman Nezamfar; Damaris Diaz; Xiaojing Xu; Virginia R. de Sa; Kenneth D. Craig; Jeannie S. Huang; Matthew S. Goodwin (EMBC, 2018)

Automated pain detection in facial videos of children using human-assisted transfer learning. - Xiaojing Xu; Kenneth Craig; Damaris Diaz; Matthew S. Goodwin; Murat Akçakaya; Busra Susam; Jeannie Huang; Virginia R. de Sa (AIH@IJCAI, 2018)

Towards automated pain detection in children using facial and electrodermal activity. - Xiaojing Xu; Busra Susam; Hooman Nezamfar; Kenneth Craig; Damaris Diaz; Jeannie Huang; Matthew S. Goodwin; Murat Akçakaya; Virginia R. de Sa (AIH@IJCAI, 2018)

Speeding up Context-based Sentence Representation Learning with Non-autoregressive Convolutional Decoding. - Shuai Tang; Hailin Jin; Chen Fang; Zhaowen Wang; Virginia R. de Sa (Rep4NLP@ACL, 2018)

Towards Classifier Visualisation in 3D Source Space. - Laurens R. Krol; Mahta Mousavi; Virginia de Sa; Thorsten O. Zander (SMC, 2018)

Multi-view Sentence Representation Learning. - Shuai Tang; Virginia R. de Sa (CoRR, 2018)

Improving Sentence Representations with Multi-view Frameworks. - Shuai Tang; Virginia R. de Sa (CoRR, 2018)

Learning Distributed Representations of Symbolic Structure Using Binding and Unbinding Operations. - Shuai Tang; Paul Smolensky; Virginia R. de Sa (CoRR, 2018)

Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning. - Shuai Tang; Virginia R. de Sa (ACL (1), 2019)

Temporally Adaptive Common Spatial Patterns with Deep Convolutional Neural Networks. - Mahta Mousavi; Virginia R. de Sa (EMBC, 2019)

Pain Evaluation in Video using Extended Multitask Learning from Multidimensional Measurements. - Xiaojing Xu; Jeannie S. Huang; Virginia R. de Sa (ML4H@NeurIPS, 2019)

An Empirical Study on Post-processing Methods for Word Embeddings. - Shuai Tang; Mahta Mousavi; Virginia R. de Sa (CoRR, 2019)

Exploring Multidimensional Measurements for Pain Evaluation using Facial Action Units. - Xiaojing Xu; Virginia R. de Sa (FG, 2020)

Deep Transfer Learning with Ridge Regression. - Shuai Tang; Virginia R. de Sa (CoRR, 2020)

Learning compact generalizable neural representations supporting perceptual grouping. - Vijay Veerabadran; Virginia R. de Sa (CoRR, 2020)

EEG Reveals Familiarity by Controlling Confidence in Memory Retrieval. - Kueida Liao; Matthew V. Mollison; Tim Curran; Virginia de Sa (CogSci, 2021)

Personalized Pain Detection in Facial Video with Uncertainty Estimation. - Xiaojing Xu; Virginia R. de Sa (EMBC, 2021)

Motor imagery performance from calibration to online control in EEG-based brain-computer interfaces. - Mahta Mousavi; Virginia R. de Sa (NER, 2021)

Multi-Subject Unsupervised Transfer with Weighted Subspace Alignment for Common Spatial Patterns. - Zhining Chen; Mahta Mousavi; Virginia R. de Sa (BCI, 2022)

Set Size Effects on the P3b in a BCI Speller. - Alessandro D'Amico; Virginia de Sa (CogSci, 2022)

Exploring the Racial Bias in Pain Detection with a Computer Vision Model. - Sarah Fabi; Xiaojing Xu; Virginia de Sa (CogSci, 2022)

Spectrally Adaptive Common Spatial Patterns. - Mahta Mousavi; Eric Lybrand; Shuangquan Feng; Shuai Tang; Rayan Saab; Virginia de Sa (CoRR, 2022)

Code O-SUKI-N 3D: Upgraded direct-drive fuel target 3D implosion code in heavy ion inertial fusion. - H. Nakamura; Ken Uchibori; Shigeo Kawata; Takahiro Karino; Virginia R. de Sa; Aleksandar I. Ogoyski (Comput. Phys. Commun., 2022)

Automated Pain Assessment in Children Using Electrodermal Activity and Video Data Fusion via Machine Learning. - Busra T. Susam; Nathan T. Riek; Murat Akçakaya; Xiaojing Xu; Virginia R. de Sa; Hooman Nezamfar; Damaris Diaz; Kenneth D. Craig; Matthew S. Goodwin; Jeannie S. Huang (IEEE Trans. Biomed. Eng., 2022)

Adaptive recurrent vision performs zero-shot computation scaling to unseen difficulty levels. - Vijay Veerabadran; Srinivas Ravishankar; Yuan Tang; Ritik Raina; Virginia de Sa (NeurIPS, 2023)

FERGI: Automatic Annotation of User Preferences for Text-to-Image Generation from Spontaneous Facial Expression Reaction. - Shuangquan Feng; Junhua Ma; Virginia R. de Sa (CoRR, 2023)

Development and Characterization of Zinc Dry Electrodes for Wearable Electrophysiology. - Cassia Rizq; Alessandro D'Amico; Aidan Truel; Joelle Faybishenko; Min Suk Lee 002; Jeong-Hoon Kim; Gert Cauwenberghs; Virginia R. de Sa (EMBC, 2024)

Image Reconstruction from Electroencephalography Using Latent Diffusion. - Teng Fei; Virginia de Sa (CoRR, 2024)

One-Frame Calibration with Siamese Network in Facial Action Unit Recognition. - Shuangquan Feng; Virginia R. de Sa (CoRR, 2024)

Decoding Imagined Handwriting from EEG. - Srinivas Ravishankar; Nora Zajzon; Virginia de Sa (CoRR, 2025)

Transferring Spatial Filters via Tangent Space Alignment in Motor Imagery BCIs. - Tekin Gunasar; Virginia de Sa (CoRR, 2025)