Richard G. Baraniuk

ORCID

Publication Activity (10 Years)

Years Active: 1989-2024
Publications (10 Years): 258

Top Venues

Publications

Shashank Sonkar, Naiming Liu, Richard G. Baraniuk
Regressive Side Effects of Training Language Models to Mimic Student Misconceptions. CoRR (2024)
Shashank Sonkar, Richard G. Baraniuk
Many-Shot Regurgitation (MSR) Prompting. CoRR (2024)
Paul M. Mayer, Lorenzo Luzi, Ali Siahkoohi, Don H. Johnson, Richard G. Baraniuk
Removing Bias from Maximum Likelihood Estimation with Model Autophagy. CoRR (2024)
Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, Richard G. Baraniuk
Pedagogical Alignment of Large Language Models. CoRR (2024)
Tam Nguyen, César A. Uribe, Tan M. Nguyen, Richard G. Baraniuk
PIDformer: Transformer Meets Control Theory. CoRR (2024)
Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi, Sina Alemohammad, Vishwanath Saragadam, Hossein Babaei, Naiming Liu, Zichao Wang, Richard G. Baraniuk
Titan: Bringing the Deep Image Prior to Implicit Representations. ICASSP (2024)
Lorenzo Luzi, Paul M. Mayer, Josue Casco-Rodriguez, Ali Siahkoohi, Richard G. Baraniuk
Boomerang: Local sampling on image manifolds using diffusion models. Trans. Mach. Learn. Res. 2024 (2024)
Shashank Sonkar, Xinghe Chen, Myco Le, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
Code Soliloquies for Accurate Calculations in Large Language Models. LAK (2024)
Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani
Asymptotics of the Sketched Pseudoinverse. SIAM J. Math. Data Sci. 6 (1) (2024)
Yehuda Dar, Daniel LeJeune, Richard G. Baraniuk
The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression. SIAM J. Math. Data Sci. 6 (2) (2024)
Shashank Sonkar, Kangqi Ni, Lesa Tran Lu, Kristi Kincaid, John S. Hutchinson, Richard G. Baraniuk
Automated Long Answer Grading with RiceChem Dataset. CoRR (2024)
Naiming Liu, Zichao Wang, Richard G. Baraniuk
Synthetic Context Generation for Question Generation. CoRR (2024)
Josue Casco-Rodriguez, Caleb Kemere, Richard G. Baraniuk
[Re] The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Non-Gaussian Observation Models. CoRR (2024)
Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. CoRR (2024)
Tan M. Nguyen, Tam Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
A Primal-Dual Framework for Transformers and Neural Networks. CoRR (2024)
Omer Ronen, Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk, Bin Yu
ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks. CoRR (2024)
Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. AIED (1) (2024)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
Deep Networks Always Grok and Here is Why. CoRR (2024)
Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
Self-Consuming Generative Models Go MAD. ICLR (2024)
T. Mitchell Roddenberry, Vishwanath Saragadam, Maarten V. de Hoop, Richard G. Baraniuk
Implicit Neural Representations and the Algebra of Complex Wavelets. ICLR (2024)
Shashank Sonkar, Kangqi Ni, Lesa Tran Lu, Kristi Kincaid, John S. Hutchinson, Richard G. Baraniuk
Automated Long Answer Grading with RiceChem Dataset. AIED (1) (2024)
Hossein Babaei, Sina Alemohammad, Richard G. Baraniuk
Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Naiming Liu, Shashank Sonkar, Myco Le, Richard G. Baraniuk
MalAlgoQA: A Pedagogical Approach for Evaluating Counterfactual Reasoning Abilities. CoRR (2024)
Shashank Sonkar, MyCo Le, Xinghe Chen, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
Code Soliloquies for Accurate Calculations in Large Language Models. CoRR (2023)
Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles. EMNLP (Findings) (2023)
Tam Nguyen, Tan M. Nguyen, Richard G. Baraniuk
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. CoRR (2023)
Tam Nguyen, Tan Nguyen, Richard G. Baraniuk
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. NeurIPS (2023)
Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
Self-Consuming Generative Models Go MAD. CoRR (2023)
Tan M. Nguyen, Tam Nguyen, Long Bui, Hai Do, Duy Khuong Nguyen, Dung D. Le, Hung Tran-The, Nhat Ho, Stanley J. Osher, Richard G. Baraniuk
A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys. ICASSP (2023)
Shashank Sonkar, Richard G. Baraniuk
Parallel Attention and Feed-Forward Net Design for Pre-training and Inference on Transformers. CoRR (2023)
Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar
Retrieval-based Controllable Molecule Generation. ICLR (2023)
Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, Richard G. Baraniuk
WIRE: Wavelet Implicit Neural Representations. CVPR (2023)
Zichao Wang, Richard G. Baraniuk
MultiQG-TI: Towards Question Generation from Multi-modal Sources. BEA@ACL (2023)
Shashank Sonkar, Zichao Wang, Richard G. Baraniuk
MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages. SustaiNLP (2023)
Shashank Sonkar, Lucy Liu, Debshila Basu Mallick, Richard G. Baraniuk
CLASS Meet SPOCK: An Education Tutoring Chatbot based on Learning Science Principles. CoRR (2023)
Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan, Richard G. Baraniuk
SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries. CoRR (2023)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
Training Dynamics of Deep Network Linear Regions. CoRR (2023)
Lorenzo Luzi, Carlos Ortiz Marrero, Nile Wynar, Richard G. Baraniuk, Michael J. Henry
Evaluating generative networks using Gaussian mixtures of image features. WACV (2023)
Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk
A Blessing of Dimensionality in Membership Inference through Regularization. AISTATS (2023)
Shashank Sonkar, Richard G. Baraniuk
Deduction under Perturbed Evidence: Probing Student Simulation Capabilities of Large Language Models. CoRR (2023)
Micah Goldblum, Anima Anandkumar, Richard G. Baraniuk, Tom Goldstein, Kyunghyun Cho, Zachary C. Lipton, Melanie Mitchell, Preetum Nakkiran, Max Welling, Andrew Gordon Wilson
Perspectives on the State and Future of Deep Learning - 2023. CoRR (2023)
T. Mitchell Roddenberry, Vishwanath Saragadam, Maarten V. de Hoop, Richard G. Baraniuk
Implicit Neural Representations and the Algebra of Complex Wavelets. CoRR (2023)
Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
A Primal-Dual Framework for Transformers and Neural Networks. ICLR (2023)
Vincent Aleven, Richard G. Baraniuk, Emma Brunskill, Scott Crossley, Dora Demszky, Stephen Fancsali, Shivang Gupta, Kenneth R. Koedinger, Chris Piech, Steven Ritter, Danielle R. Thomas, Simon Woodhead, Wanli Xing
Towards the Future of AI-Augmented Human Tutoring in Math Learning. AIED (Posters/Late Breaking Results/...) (2023)
Fernando Gama, Nicolas Zilberstein, Martin Sevilla, Richard G. Baraniuk, Santiago Segarra
Unsupervised Learning of Sampling Distributions for Particle Filters. IEEE Trans. Signal Process. 71 (2023)
Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, Richard G. Baraniuk
WIRE: Wavelet Implicit Neural Representations. CoRR (2023)
Naiming Liu, Shashank Sonkar, Zichao Wang, Simon Woodhead, Richard G. Baraniuk
Novice Learner and Expert Tutor: Evaluating Math Reasoning Abilities of Large Language Models with Misconceptions. CoRR (2023)
Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan, Richard G. Baraniuk
SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries. CVPR (2023)
Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Klinton Bicknell, Jeremy Roschelle, Ben Motz, Danielle S. McNamara, Richard G. Baraniuk, Debshila Basu Mallick, René F. Kizilcec, Ryan Baker, Stephen Fancsali, April Murphy
Fourth Annual Workshop on A/B Testing and Platform-Enabled Learning Research. L@S (2023)
Katie Bainbridge, Candace A. Walkington, Armon Ibrahim, Iris Zhong, Debshila Basu Mallick, Julianna Washington, Richard G. Baraniuk
A Case Study using Large Language Models to Generate Metadata for Math Questions. LLM@AIED (2023)
Brittany C. Bradford, Debshila Basu Mallick, Richard G. Baraniuk
Unlocking Financial Success: Empowering Higher Ed Students and Developing Financial Literacy Interventions at Scale. L@S (2023)
Zichao Wang, Richard G. Baraniuk
MultiQG-TI: Towards Question Generation from Multi-modal Sources. CoRR (2023)
Debshila Basu Mallick, Brittany C. Bradford, Richard G. Baraniuk
Secure Education and Learning Research at Scale with OpenStax Kinetic. L@S (2023)
Shashank Sonkar, Richard G. Baraniuk
Deduction under Perturbed Evidence: Probing Student Simulation (Knowledge Tracing) Capabilities of Large Language Models. LLM@AIED (2023)
Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. ICASSP (2022)
Yehuda Dar, Richard G. Baraniuk
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. SIAM J. Math. Data Sci. 4 (4) (2022)
Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CVPR (2022)
Shashank Sonkar, Naiming Liu, Richard G. Baraniuk
A Visual Tour Of Current Challenges In Multimodal Language Models. CoRR (2022)
Cj Barberan, Sina Alemmohammad, Naiming Liu, Randall Balestriero, Richard G. Baraniuk
NeuroView-RNN: It's About Time. FAccT (2022)
Zichao Wang, Jakob Valdez, Debshila Basu Mallick, Richard G. Baraniuk
Towards Human-Like Educational Question Generation with Large Language Models. AIED (1) (2022)
Rudolf H. Riedi, Randall Balestriero, Richard G. Baraniuk
Singular Value Perturbation and Deep Network Optimization. CoRR (2022)
Sina Alemohammad, Hossein Babaei, C. J. Barberan, Naiming Liu, Lorenzo Luzi, Blake Mason, Richard G. Baraniuk
NFT-K: Non-Fungible Tangent Kernels. ICASSP (2022)
Lorenzo Luzi, Ali Siahkoohi, Paul M. Mayer, Josue Casco-Rodriguez, Richard G. Baraniuk
Boomerang: Local sampling on image manifolds using diffusion models. CoRR (2022)
Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan
Automated Scoring for Reading Comprehension via In-context BERT Tuning. AIED (1) (2022)
T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra
On Local Distributions in Graph Signal Processing. IEEE Trans. Signal Process. 70 (2022)
Tan Minh Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang
Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. MSML (2022)
Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk
Benign Overparameterization in Membership Inference with Early Stopping. CoRR (2022)
Vishwanath Saragadam, Randall Balestriero, Ashok Veeraraghavan, Richard G. Baraniuk
DeepTensor: Low-Rank Tensor Decomposition with Deep Network Priors. CoRR (2022)
Naiming Liu, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
Open-Ended Knowledge Tracing. CoRR (2022)
Naiming Liu, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
Open-ended Knowledge Tracing for Computer Science Education. EMNLP (2022)
Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan
Automated Scoring for Reading Comprehension via In-context BERT Tuning. CoRR (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. CoRR (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values. CoRR (2022)
Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Ben Motz, Debshila Basu Mallick, Klinton Bicknell, Danielle S. McNamara, René F. Kizilcec, Jeremy Roschelle, Richard G. Baraniuk, Ryan Baker
Third Annual Workshop on A/B Testing and Platform-Enabled Learning Research. L@S (2022)
Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan, Richard G. Baraniuk, Ashok Veeraraghavan
MINER: Multiscale Implicit Neural Representation. ECCV (23) (2022)
Tan Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang
Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. CoRR (2022)
Randall Balestriero, Richard G. Baraniuk
Batch Normalization Explained. CoRR (2022)
C. J. Barberan, Sina Alemohammad, Naiming Liu, Randall Balestriero, Richard G. Baraniuk
NeuroView-RNN: It's About Time. CoRR (2022)
Ali Mousavi, Richard G. Baraniuk
Uniform Partitioning of Data Grid for Association Detection. IEEE Trans. Pattern Anal. Mach. Intell. 44 (2) (2022)
David J. Brenes, C. J. Barberan, Brady Hunt, Sonia G. Parra, Mila P. Salcedo, Júlio C. Possati-Resende, Miriam L. Cremer, Philip E. Castle, José H. T. G. Fregnani, Mauricio Maza, Kathleen M. Schmeler, Richard G. Baraniuk, Rebecca Richards-Kortum
Multi-task network for automated analysis of high-resolution endomicroscopy images to detect cervical precancer and cancer. Comput. Medical Imaging Graph. 97 (2022)
Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani
Asymptotics of the Sketched Pseudoinverse. CoRR (2022)
Vishwanath Saragadam, Zheyi Han, Vivek Boominathan, Luocheng Huang, Shiyu Tan, Johannes E. Fröch, Karl F. Böhringer, Richard G. Baraniuk, Arka Majumdar, Ashok Veeraraghavan
Foveated Thermal Computational Imaging in the Wild Using All-Silicon Meta-Optics. CoRR (2022)
Jasper Tan, Blake Mason, Hamid Javadi, Richard G. Baraniuk
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference. NeurIPS (2022)
Haoran You, Randall Balestriero, Zhihan Lu, Yutong Kou, Huihong Shi, Shunyao Zhang, Shang Wu, Yingyan Lin, Richard G. Baraniuk
Max-Affine Spline Insights Into Deep Network Pruning. Trans. Mach. Learn. Res. 2022 (2022)
Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan, Richard G. Baraniuk, Ashok Veeraraghavan
MINER: Multiscale Implicit Neural Representations. CoRR (2022)
Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CoRR (2022)
Ángel Bueno Rodríguez, Randall Balestriero, Silvio De Angelis, M. Carmen Benítez, Luciano Zuccarello, Richard G. Baraniuk, Jesús M. Ibáñez, Maarten V. de Hoop
Recurrent Scattering Network Detects Metastable Behavior in Polyphonic Seismo-Volcanic Signals for Volcano Eruption Forecasting. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Bao Wang, Tan M. Nguyen, Tao Sun, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. SIAM J. Imaging Sci. 15 (2) (2022)
Tam Minh Nguyen, Tan Minh Nguyen, Dung D. D. Le, Duy Khuong Nguyen, Viet-Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher
Improving Transformers with Probabilistic Attention Keys. ICML (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining. ICLR (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values. CVPR (2022)
Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
Spatial Transformer K-Means. CoRR (2022)
Pavan K. Kota, Daniel LeJeune, Rebekah A. Drezek, Richard G. Baraniuk
Extreme Compressed Sensing of Poisson Rates From Multiple Measurements. IEEE Trans. Signal Process. 70 (2022)
Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar
Retrieval-based Controllable Molecule Generation. CoRR (2022)
Jasper Tan, Blake Mason, Hamid Javadi, Richard G. Baraniuk
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference. CoRR (2022)
Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
Spatial Transformer K-Means. IEEECONF (2022)
T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra
On Local Distributions in Graph Signal Processing. CoRR (2022)
Shashank Sonkar, Zichao Wang, Richard G. Baraniuk
MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages. CoRR (2022)
Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra
Unrolling Particles: Unsupervised Learning of Sampling Distributions. ICASSP (2022)
Yehuda Dar, Lorenzo Luzi, Richard G. Baraniuk
Overfreezing Meets Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural Networks. CoRR (2022)

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Publication Activity (10 Years)

Top Topics

Top Venues

Richard G. Baraniuk