Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts. - Kang, Junmo; Karlinsky, Leonid; Luo, Hongyin; Wang, Zhen; Hansen, Jacob A.; Glass, James R.; Cox, David Daniel; Panda, Rameswar; Feris, Rogério; Ritter, Alan (2025)

Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search. - Shen, Maohao; Zeng, Guangtao; Qi, Zhenting; Hong, Zhang-Wei; Chen, Zhenfang; Lu, Wei; Wornell, Gregory W.; Das, Subhro; Cox, David; Gan, Chuang (CoRR, 2025)

Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence. - Karlinsky, Leonid; Arbelle, Assaf; Daniels, Abraham; Nassar, Ahmed; Alfassi, Amit; Wu, Bo; Schwartz, Eli; Joshi, Dhiraj; Kondic, Jovana; Shabtay, Nimrod; Li, Pengyuan; Herzig, Roei; et al. (CoRR, 2025)

Granite Embedding Models. - Awasthy, Parul; Trivedi, Aashka; Li, Yulong; Bornea, Mihaela A.; Cox, David; Daniels, Abraham; Franz, Martin; Goodhart, Gabe; Iyer, Bhavani; Kumar, Vishwajeet; Lastras, Luis A.; McCarley, J. Scott; et al. (CoRR, 2025)

Activated LoRA: Fine-tuned LLMs for Intrinsics. - Greenewald, Kristjan; Lastras, Luis A.; Parnell, Thomas; Shah, Vraj; Popa, Lucian; Zizzo, Giulio; Gunasekara, R. Chulaka; Rawat, Ambrish; Cox, David (CoRR, 2025)

Satori-SWE: Evolutionary Test-Time Scaling for Sample-Efficient Software Engineering. - Zeng, Guangtao; Shen, Maohao; Chen, Delin; Qi, Zhenting; Das, Subhro; Gutfreund, Dan; Cox, David; Wornell, Gregory W.; Lu, Wei; Hong, Zhang-Wei; Gan, Chuang (CoRR, 2025)

A System for Accurate Tracking and Video Recordings of Rodent Eye Movements using Convolutional Neural Networks for Biomedical Image Segmentation. - Puri, Isha; Cox, David D. (CoRR, 2025)

Granite Embedding R2 Models. - Awasthy, Parul; Trivedi, Aashka; Li, Yulong; Doshi, Meet; Bhat, Riyaz A.; P, Vignesh; Kumar, Vishwajeet; Yang, Yushu; Iyer, Bhavani; Daniels, Abraham; Murthy, Rudra; Barker, Ken; et al. (CoRR, 2025)

Self-Specialization: Uncovering Latent Expertise within Large Language Models. - Kang, Junmo; Luo, Hongyin; Zhu, Yada; Hansen, Jacob A.; Glass, James R.; Cox, David D.; Ritter, Alan; Feris, Rogério; Karlinsky, Leonid (2024)

Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks. - Abdelaziz, Ibrahim; Basu, Kinjal; Agarwal, Mayank; Kumaravel, Sadhana; Stallone, Matthew; Panda, Rameswar; Rizk, Yara; Bhargav, G. P. Shrivatsa; Crouse, Maxwell; Gunasekara, R. Chulaka; Ikbal, Shajith; Joshi, Sachindra; et al. (2024)

Breakthrough Low-Latency, High-Energy-Efficiency LLM Inference Performance Using NorthPole. - Appuswamy, Rathinakumar; DeBole, Michael V.; Taba, Brian; Esser, Steven K.; Cassidy, Andrew S.; Amir, Arnon; Andreopoulos, Alexander; Bablani, Deepika; Datta, Pallab; Kusnitz, Jeffrey A.; McClatchey, Nathaniel J.; McGlohon, Neil; et al. (2024)

SALMON: Self-Alignment with Instructable Reward Models. - Sun, Zhiqing; Shen, Yikang; Zhang, Hongxin; Zhou, Qinhong; Chen, Zhenfang; Cox, David Daniel; Yang, Yiming; Gan, Chuang (2024)

Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning. - Wang, Runqian; Ghosh, Soumya; Cox, David D.; Antognini, Diego; Oliva, Aude; Feris, Rogério; Karlinsky, Leonid (2024)

LAB: Large-Scale Alignment for ChatBots. - Sudalairaj, Shivchander; Bhandwaldar, Abhishek; Pareja, Aldo; Xu, Kai; Cox, David D.; Srivastava, Akash (CoRR, 2024)

Granite Code Models: A Family of Open Foundation Models for Code Intelligence. - Mishra, Mayank; Stallone, Matt; Zhang, Gaoyuan; Shen, Yikang; Prasad, Aditya; Soria, Adriana Meza; Merler, Michele; Selvam, Parameswaran; Surendran, Saptha; Singh, Shivdeep; Sethi, Manish; Dang, Xuan-Hong; et al. (CoRR, 2024)

Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning. - Wang, Runqian; Ghosh, Soumya; Cox, David D.; Antognini, Diego; Oliva, Aude; Feris, Rogério; Karlinsky, Leonid (CoRR, 2024)

Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts. - Kang, Junmo; Karlinsky, Leonid; Luo, Hongyin; Wang, Zhen; Hansen, Jacob A.; Glass, Jim; Cox, David D.; Panda, Rameswar; Feris, Rogério; Ritter, Alan (CoRR, 2024)

Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks. - Abdelaziz, Ibrahim; Basu, Kinjal; Agarwal, Mayank; Kumaravel, Sadhana; Stallone, Matthew; Panda, Rameswar; Rizk, Yara; Bhargav, GP; Crouse, Maxwell; Gunasekara, R. Chulaka; Ikbal, Shajith; Joshi, Sachin; et al. (CoRR, 2024)

The infrastructure powering IBM's Gen AI model development. - Gershon, Talia; Seelam, Seetharami; Belgodere, Brian; Bonilla, Milton; Hoang, Lan; Barnett, Danny; Chung, I-Hsin; Mohan, Apoorve; Chen, Ming-Hung; Luo, Lixiang; Walkup, Robert; Evangelinos, Constantinos; et al. (CoRR, 2024)

Scaling Granite Code Models to 128K Context. - Stallone, Matt; Saxena, Vaibhav; Karlinsky, Leonid; McGinn, Bridget; Bula, Tim; Mishra, Mayank; Soria, Adriana Meza; Zhang, Gaoyuan; Prasad, Aditya; Shen, Yikang; Surendran, Saptha; Guttula, Shanmukha C.; et al. (CoRR, 2024)

Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Scheduler. - Shen, Yikang; Stallone, Matthew; Mishra, Mayank; Zhang, Gaoyuan; Tan, Shawn; Prasad, Aditya; Soria, Adriana Meza; Cox, David D.; Panda, Rameswar (CoRR, 2024)

Audio-Visual Neural Syntax Acquisition. - Lai, Cheng-I Jeff; Shi, Freda; Peng, Puyuan; Kim, Yoon; Gimpel, Kevin; Chang, Shiyu; Chuang, Yung-Sung; Bhati, Saurabhchand; Cox, David D.; Harwath, David; Zhang, Yang; Livescu, Karen; et al. (2023)

ConStruct-VL: Data-Free Continual Structured VL Concepts Learning. - Smith, James Seale; Cascante-Bonilla, Paola; Arbelle, Assaf; Kim, Donghyun; Panda, Rameswar; Cox, David D.; Yang, Diyi; Kira, Zsolt; Feris, Rogério; Karlinsky, Leonid (2023)

Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness. - Dapello, Joel; Kar, Kohitij; Schrimpf, Martin; Geary, Robert Baldwin; Ferguson, Michael; Cox, David Daniel; DiCarlo, James J. (2023)

Learning to Grow Pretrained Models for Efficient Transformer Training. - Wang, Peihao; Panda, Rameswar; Hennigen, Lucas Torroba; Greengard, Philip; Karlinsky, Leonid; Feris, Rogério; Cox, David Daniel; Wang, Zhangyang; Kim, Yoon (2023)

Rapid Development of Compositional AI. - Martie, Lee; Rosenberg, Jessie; Demers, Veronique; Zhang, Gaoyuan; Bhardwaj, Onkar; Henning, John; Prasad, Aditya; Stallone, Matt; Lee, Ja Young; Yip, Lucy; Adesina, Damilola; Paikari, Elahe; et al. (2023)

Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision. - Sun, Zhiqing; Shen, Yikang; Zhou, Qinhong; Zhang, Hongxin; Chen, Zhenfang; Cox, David D.; Yang, Yiming; Gan, Chuang (2023)

Rapid Development of Compositional AI. - Martie, Lee; Rosenberg, Jessie; Demers, Veronique; Zhang, Gaoyuan; Bhardwaj, Onkar; Henning, John; Prasad, Aditya; Stallone, Matt; Lee, Ja Young; Yip, Lucy; Adesina, Damilola; Paikari, Elahe; et al. (CoRR, 2023)

Learning to Grow Pretrained Models for Efficient Transformer Training. - Wang, Peihao; Panda, Rameswar; Hennigen, Lucas Torroba; Greengard, Philip; Karlinsky, Leonid; Feris, Rogério; Cox, David Daniel; Wang, Zhangyang; Kim, Yoon (CoRR, 2023)

Embodied Concept Learner: Self-supervised Learning of Concepts and Mapping through Instruction Following. - Ding, Mingyu; Xu, Yan; Chen, Zhenfang; Cox, David Daniel; Luo, Ping; Tenenbaum, Joshua B.; Gan, Chuang (CoRR, 2023)

Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision. - Sun, Zhiqing; Shen, Yikang; Zhou, Qinhong; Zhang, Hongxin; Chen, Zhenfang; Cox, David D.; Yang, Yiming; Gan, Chuang (CoRR, 2023)

Self-Specialization: Uncovering Latent Expertise within Large Language Models. - Kang, Junmo; Luo, Hongyin; Zhu, Yada; Glass, James R.; Cox, David D.; Ritter, Alan; Feris, Rogério; Karlinsky, Leonid (CoRR, 2023)

SALMON: Self-Alignment with Principle-Following Reward Models. - Sun, Zhiqing; Shen, Yikang; Zhang, Hongxin; Zhou, Qinhong; Chen, Zhenfang; Cox, David D.; Yang, Yiming; Gan, Chuang (CoRR, 2023)

Audio-Visual Neural Syntax Acquisition. - Lai, Cheng-I Jeff; Shi, Freda; Peng, Puyuan; Kim, Yoon; Gimpel, Kevin; Chang, Shiyu; Chuang, Yung-Sung; Bhati, Saurabhchand; Cox, David D.; Harwath, David; Zhang, Yang; Livescu, Karen; et al. (CoRR, 2023)

An Adversarial Framework for Generating Unseen Images by Activation Maximization. - Zhang, Yang; Zhou, Wang; Zhang, Gaoyuan; Cox, David D.; Chang, Shiyu (2022)

Embodied Concept Learner: Self-supervised Learning of Concepts and Mapping through Instruction Following. - Ding, Mingyu; Xu, Yan; Chen, Zhenfang; Cox, David Daniel; Luo, Ping; Tenenbaum, Joshua B.; Gan, Chuang (2022)

VALHALLA: Visual Hallucination for Machine Translation. - Li, Yi; Panda, Rameswar; Kim, Yoon; Chen, Chun-Fu Richard; Feris, Rogério; Cox, David D.; Vasconcelos, Nuno (2022)

On the Interplay between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis. - Lai, Cheng-I Jeff; Cooper, Erica; Zhang, Yang; Chang, Shiyu; Qian, Kaizhi; Liao, Yi-Lun; Chuang, Yung-Sung; Liu, Alexander H.; Yamagishi, Junichi; Cox, David D.; Glass, James R. (2022)

ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers. - Qian, Kaizhi; Zhang, Yang; Gao, Heting; Ni, Junrui; Lai, Cheng-I; Cox, David D.; Hasegawa-Johnson, Mark; Chang, Shiyu (2022)

Improving Self-Supervised Speech Representations by Disentangling Speakers. - Qian, Kaizhi; Zhang, Yang; Gao, Heting; Ni, Junrui; Lai, Cheng-I; Cox, David D.; Hasegawa-Johnson, Mark; Chang, Shiyu (CoRR, 2022)

VALHALLA: Visual Hallucination for Machine Translation. - Li, Yi; Panda, Rameswar; Kim, Yoon; Chen, Chun-Fu; Feris, Rogério; Cox, David D.; Vasconcelos, Nuno (CoRR, 2022)

ConStruct-VL: Data-Free Continual Structured VL Concepts Learning. - Smith, James Seale; Cascante-Bonilla, Paola; Arbelle, Assaf; Kim, Donghyun; Panda, Rameswar; Cox, David D.; Yang, Diyi; Kira, Zsolt; Feris, Rogério; Karlinsky, Leonid (CoRR, 2022)

Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. - Abrevaya, Germán; Dumas, Guillaume; Aravkin, Aleksandr Y.; Zheng, Peng; Gagnon-Audet, Jean-Christophe; Kozloski, James R.; Polosecki, Pablo; Lajoie, Guillaume; Cox, David D.; Dawson, Silvina Ponce; Cecchi, Guillermo A.; Rish, Irina (Neural Comput., 2021)

Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators. - Fu, Yonggan; Zhang, Yongan; Zhang, Yang; Cox, David D.; Lin, Yingyan (2021)

Global Prosody Style Transfer Without Text Transcriptions. - Qian, Kaizhi; Zhang, Yang; Chang, Shiyu; Xiong, Jinjun; Gan, Chuang; Cox, David D.; Hasegawa-Johnson, Mark (2021)

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks. - Fu, Yonggan; Yu, Qixuan; Zhang, Yang; Wu, Shang; Ouyang, Xu; Cox, David D.; Lin, Yingyan (2021)

Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception. - Dapello, Joel; Feather, Jenelle; Le, Hang; Marques, Tiago; Cox, David D.; McDermott, Josh H.; DiCarlo, James J.; Chung, SueYeon (2021)

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. - Gan, Chuang; Schwartz, Jeremy; Alter, Seth; Mrowca, Damian; Schrimpf, Martin; Traer, James; Freitas, Julian De; Kubilius, Jonas; Bhandwaldar, Abhishek; Haber, Nick; Sano, Megumi; Kim, Kuno; et al. (2021)

PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition. - Lai, Cheng-I Jeff; Zhang, Yang; Liu, Alexander H.; Chang, Shiyu; Liao, Yi-Lun; Chuang, Yung-Sung; Qian, Kaizhi; Khurana, Sameer; Cox, David D.; Glass, James R. (2021)

Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences. - VidalMata, Rosaura G.; Scheirer, Walter J.; Kukleva, Anna; Cox, David D.; Kuehne, Hilde (2021)

PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition. - Lai, Cheng-I Jeff; Zhang, Yang; Liu, Alexander H.; Chang, Shiyu; Liao, Yi-Lun; Chuang, Yung-Sung; Qian, Kaizhi; Khurana, Sameer; Cox, David D.; Glass, James R. (CoRR, 2021)

Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators. - Fu, Yonggan; Zhang, Yongan; Zhang, Yang; Cox, David D.; Lin, Yingyan (CoRR, 2021)

Global Rhythm Style Transfer Without Text Transcriptions. - Qian, Kaizhi; Zhang, Yang; Chang, Shiyu; Xiong, Jinjun; Gan, Chuang; Cox, David D.; Hasegawa-Johnson, Mark (CoRR, 2021)

On the Interplay Between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis. - Lai, Cheng-I Jeff; Cooper, Erica; Zhang, Yang; Chang, Shiyu; Qian, Kaizhi; Liao, Yi-Lun; Chuang, Yung-Sung; Liu, Alexander H.; Yamagishi, Junichi; Cox, David D.; Glass, James R. (CoRR, 2021)

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks. - Fu, Yonggan; Yu, Qixuan; Zhang, Yang; Wu, Shang; Ouyang, Xu; Cox, David D.; Lin, Yingyan (CoRR, 2021)

Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception. - Dapello, Joel; Feather, Jenelle; Le, Hang; Marques, Tiago; Cox, David D.; McDermott, Josh H.; DiCarlo, James J.; Chung, SueYeon (CoRR, 2021)

Experiences and Insights for Collaborative Industry-Academic Research in Artificial Intelligence. - Amini, Lisa; Chen, Ching-Hua; Cox, David D.; Oliva, Aude; Torralba, Antonio (AI Mag., 2020)

A neural network trained for prediction mimics diverse features of biological neurons and perception. - Lotter, William; Kreiman, Gabriel; Cox, David D. (Nat. Mach. Intell., 2020)

Unsupervised Speech Decomposition via Triple Information Bottleneck. - Qian, Kaizhi; Zhang, Yang; Chang, Shiyu; Hasegawa-Johnson, Mark; Cox, David D. (2020)

Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations. - Dapello, Joel; Marques, Tiago; Schrimpf, Martin; Geiger, Franziska; Cox, David D.; DiCarlo, James J. (2020)

Unsupervised Speech Decomposition via Triple Information Bottleneck. - Qian, Kaizhi; Zhang, Yang; Chang, Shiyu; Cox, David D.; Hasegawa-Johnson, Mark (CoRR, 2020)

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. - Gan, Chuang; Schwartz, Jeremy; Alter, Seth; Schrimpf, Martin; Traer, James; Freitas, Julian De; Kubilius, Jonas; Bhandwaldar, Abhishek; Haber, Nick; Sano, Megumi; Kim, Kuno; Wang, Elias; et al. (CoRR, 2020)

Lifelong Object Detection. - Zhou, Wang; Chang, Shiyu; Sosa, Norma E.; Hamann, Hendrik F.; Cox, David D. (CoRR, 2020)

not-so-BigGAN: Generating High-Fidelity Images on a Small Compute Budget. - Han, Seungwook; Srivastava, Akash; Hurwitz, Cole L.; Sattigeri, Prasanna; Cox, David D. (CoRR, 2020)

Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling. - Srivastava, Akash; Bansal, Yamini; Ding, Yukun; Hurwitz, Cole L.; Xu, Kai; Egger, Bernhard; Sattigeri, Prasanna; Tenenbaum, Josh; Cox, David D.; Gutfreund, Dan (CoRR, 2020)

Object-Centric Diagnosis of Visual Reasoning. - Yang, Jianwei; Mao, Jiayuan; Wu, Jiajun; Parikh, Devi; Cox, David D.; Tenenbaum, Joshua B.; Gan, Chuang (CoRR, 2020)

Self-Supervised Moving Vehicle Tracking With Stereo Sound. - Gan, Chuang; Zhao, Hang; Chen, Peihao; Cox, David D.; Torralba, Antonio (2019)

More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation. - Fan, Quanfu; Chen, Chun-Fu (Richard); Kuehne, Hilde; Pistoia, Marco; Cox, David D. (2019)

ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. - Chen, Xiangyi; Liu, Sijia; Xu, Kaidi; Li, Xingguo; Lin, Xue; Hong, Mingyi; Cox, David D. (2019)

Triton: an intermediate language and compiler for tiled neural network computations. - Tillet, Philippe; Kung, Hsiang-Tsung; Cox, David D. (2019)

ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. - Chen, Xiangyi; Liu, Sijia; Xu, Kaidi; Li, Xingguo; Lin, Xue; Hong, Mingyi; Cox, David D. (CoRR, 2019)

Self-supervised Moving Vehicle Tracking with Stereo Sound. - Gan, Chuang; Zhao, Hang; Chen, Peihao; Cox, David D.; Torralba, Antonio (CoRR, 2019)

SimVAE: Simulator-Assisted Training forInterpretable Generative Models. - Srivastava, Akash; Rosenberg, Jessie C.; Gutfreund, Dan; Cox, David D. (CoRR, 2019)

More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation. - Fan, Quanfu; Chen, Chun-Fu; Kuehne, Hilde; Pistoia, Marco; Cox, David D. (CoRR, 2019)

A System for Accurate Tracking and Video Recordings of Rodent Eye Movements using Convolutional Neural Networks for Biomedical Image Segmentation. - Puri, Isha; Cox, David D. (2018)

On the Information Bottleneck Theory of Deep Learning. - Saxe, Andrew M.; Bansal, Yamini; Dapello, Joel; Advani, Madhu; Kolchinsky, Artemy; Tracey, Brendan D.; Cox, David D. (2018)

Conditional Infilling GANs for Data Augmentation in Mammogram Classification. - Wu, Eric; Wu, Kevin; Cox, David D.; Lotter, William (2018)

Input-Aware Auto-Tuning of Compute-Bound HPC Kernels. - Tillet, Philippe; Cox, David D. (CoRR, 2018)

A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception. - Lotter, William; Kreiman, Gabriel; Cox, David D. (CoRR, 2018)

Minnorm training: an algorithm for training over-parameterized deep neural networks. - Bansal, Yamini; Advani, Madhu; Cox, David D.; Saxe, Andrew M. (CoRR, 2018)

Conditional Infilling GANs for Data Augmentation in Mammogram Classification. - Wu, Eric; Wu, Kevin; Cox, David D.; Lotter, William (CoRR, 2018)

Infomax-ICA using Hessian-free optimization. - Tillet, Philippe; Kung, H. T.; Cox, David D. (2017)

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. - Lotter, William; Kreiman, Gabriel; Cox, David D. (2017)

A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification. - Lotter, William; Sorensen, Greg; Cox, David D. (2017)

Input-aware auto-tuning of compute-bound HPC kernels. - Tillet, Philippe; Cox, David D. (2017)

Using Human Brain Activity to Guide Machine Learning. - Fong, Ruth; Scheirer, Walter J.; Cox, David D. (CoRR, 2017)

Recurrent computations for visual pattern completion. - Tang, Hanlin; Lotter, Bill; Schrimpf, Martin; Paredes, Ana; Caro, Josue Ortega; Hardesty, Walter; Cox, David D.; Kreiman, Gabriel (CoRR, 2017)

A Multi-Scale CNN and Curriculum Learning Strategy for Mammogram Classification. - Lotter, William; Sorensen, Greg; Cox, David D. (CoRR, 2017)

Fine-tuning Deep Belief Networks using Harmony Search. - Papa, João Paulo; Scheirer, Walter J.; Cox, David Daniel (Appl. Soft Comput., 2016)

Visual Place Recognition: A Survey. - Lowry, Stephanie M.; Sünderhauf, Niko; Newman, Paul; Leonard, John J.; Cox, David D.; Corke, Peter I.; Milford, Michael J. (IEEE Trans. Robotics, 2016)

Tensor Switching Networks. - Tsai, Chuan-Yung; Saxe, Andrew M.; Cox, David D. (2016)

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. - Lotter, William; Kreiman, Gabriel; Cox, David D. (CoRR, 2016)

Tensor Switching Networks. - Tsai, Chuan-Yung; Saxe, Andrew M.; Cox, David D. (CoRR, 2016)

Model selection for Discriminative Restricted Boltzmann Machines through meta-heuristic techniques. - Papa, João Paulo; Rosa, Gustavo H.; Marana, Aparecido Nilceu; Scheirer, Walter J.; Cox, David D. (J. Comput. Sci., 2015)

Improving Optimum-Path Forest Classification Using Confidence Measures. - Fernandes, Silas Evandro Nachif; Scheirer, Walter J.; Cox, David D.; Papa, João Paulo (2015)

Fine-Tuning Convolutional Neural Networks Using Harmony Search. - Rosa, Gustavo H.; Papa, João Paulo; Marana, Aparecido Nilceu; Scheirer, Walter J.; Cox, David D. (2015)

On the Model Selection of Bernoulli Restricted Boltzmann Machines Through Harmony Search. - Papa, João P.; Rosa, Gustavo Henrique; Costa, Kelton A. P.; Marana, Nilceu A.; Scheirer, Walter J.; Cox, David Daniel (2015)

Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework. - Tsai, Chuan-Yung; Cox, David D. (CoRR, 2015)

Unsupervised Learning of Visual Structure using Predictive Generative Networks. - Lotter, William; Kreiman, Gabriel; Cox, David D. (CoRR, 2015)

Vision-based Simultaneous Localization and Mapping in Changing Outdoor Environments. - Milford, Michael; Vig, Eleonora; Scheirer, Walter J.; Cox, David D. (J. Field Robotics, 2014)

Perceptual Annotation: Measuring Human Vision to Improve Computer Vision. - Scheirer, Walter J.; Anthony, Samuel E.; Nakayama, Ken; Cox, David D. (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Learning Person-Specific Representations From Faces in the Wild. - Chiachia, Giovani; Falcão, Alexandre X.; Pinto, Nicolas; Rocha, Anderson; Cox, David D. (IEEE Trans. Inf. Forensics Secur., 2014)

Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images. - Vig, Eleonora; Dorr, Michael; Cox, David D. (2014)

Condition-invariant, top-down visual place recognition. - Milford, Michael; Scheirer, Walter J.; Vig, Eleonora; Glover, Arren; Baumann, Oliver; Mattingley, Jason B.; Cox, David D. (2014)

The 2013 face recognition evaluation in mobile environment. - Günther, Manuel; Costa-Pazo, Artur; Ding, Changxing; Boutellaa, Elhocine; Chiachia, Giovani; Zhang, Honglei; Angeloni, Marcus A.; Struc, Vitomir; Khoury, Elie; Vázquez-Fernández, Esteban; Tao, Dacheng; Bengherabi, Messaoud; et al. (2013)

Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures. - Bergstra, James; Yamins, Daniel; Cox, David D. (2013)

Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms. - Bergstra, James; Yamins, Dan; Cox, David D. (2013)

SkData: Data Sets and Algorithm Evaluation Protocols in Python. - Bergstra, James; Pinto, Nicolas; Cox, David D. (2013)

Hyperparameter Optimization and Boosting for Classifying Facial Expressions: How good can a "Null" Model be? - Bergstra, James; Cox, David D. (CoRR, 2013)

High-throughput-derived biologically-inspired features for unconstrained face recognition. - Pinto, Nicolas; Cox, David D. (Image Vis. Comput., 2012)

Person-Specific Subspace Analysis for Unconstrained Familiar Face Identification. - Chiachia, Giovani; Pinto, Nicolas; Schwartz, William Robson; Rocha, Anderson; Falcão, Alexandre X.; Cox, David D. (2012)

Space-Variant Descriptor Sampling for Action Recognition Based on Saliency and Eye Movements. - Vig, Eleonora; Dorr, Michael; Cox, David D. (2012)

Saliency-based selection of sparse descriptors for action recognition. - Vig, Eleonora; Dorr, Michael; Cox, David D. (2012)

Making a Science of Model Search - Bergstra, James; Yamins, Dan; Cox, David D. (CoRR, 2012)

Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook. - Pinto, Nicolas; Stone, Zak; Zickler, Todd E.; Cox, David D. (2011)

Beyond simple features: A large-scale feature search approach to unconstrained face recognition. - Cox, David D.; Pinto, Nicolas (2011)

Comparing state-of-the-art visual features on invariant object recognition tasks. - Pinto, Nicolas; Barhomi, Youssef; Cox, David D.; DiCarlo, James J. (2011)

An Evaluation of the Invariance Properties of a Biologically-Inspired System for Unconstrained Face Recognition. - Pinto, Nicolas; Cox, David D. (2010)

Towards an embedded biologically-inspired machine vision processor. - Sriram, Vinay; Cox, David D.; Tsoi, Kuen Hung; Luk, Wayne (2010)

A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation. - Pinto, Nicolas; Doukhan, David; DiCarlo, James J.; Cox, David D. (PLoS Comput. Biol., 2009)

How far can you get with a modern face recognition test set using only simple features?. - Pinto, Nicolas; DiCarlo, James J.; Cox, David D. (2009)

Why is Real-World Visual Object Recognition Hard? - Pinto, Nicolas; Cox, David D.; DiCarlo, James J. (PLoS Comput. Biol., 2008)

Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex. - Cox, David D.; Savoy, Robert L. (NeuroImage, 2003)