Multiagent Coordination for Energy Consumption Scheduling in Consumer Cooperatives. - Andreas Veit; Ying Xu; Ronghuo Zheng; Nilanjan Chakraborty; Katia P. Sycara (AAAI, 2013)

Household electricity demand forecasting: benchmarking state-of-the-art methods. - Andreas Veit; Christoph Goebel; Rohit Tidke; Christoph Doblander; Hans-Arno Jacobsen (e-Energy, 2014)

Demand Side Energy Management via Multiagent Coordination in Consumer Cooperatives. - Andreas Veit; Ying Xu; Ronghuo Zheng; Nilanjan Chakraborty; Katia P. Sycara (J. Artif. Intell. Res., 2014)

Learning Visual Clothing Style with Heterogeneous Dyadic Co-Occurrences. - Andreas Veit; Balazs Kovacs; Sean Bell; Julian J. McAuley; Kavita Bala; Serge J. Belongie (ICCV, 2015)

MDSM: Generalized multiagent coordination for demand side management. - Andreas Veit (SmartGridComm, 2015)

Multi-agent device-level modeling framework for demand scheduling. - Andreas Veit; Hans-Arno Jacobsen (SmartGridComm, 2015)

On Optimizing Human-Machine Task Assignments. - Andreas Veit; Michael J. Wilber; Rajan Vaish; Serge J. Belongie; James Davis 001; Vishal Anand 002; Anshu Aviral; Prithvijit Chakrabarty; Yash Chandak; Sidharth Chaturvedi; Chinmaya Devaraj; Ankit Dhall; et al. (CoRR, 2015)

Learning to Detect and Match Keypoints with Deep Architectures. - Hani Altwaijry; Andreas Veit; Serge J. Belongie (BMVC, 2016)

Residual Networks Behave Like Ensembles of Relatively Shallow Networks. - Andreas Veit; Michael J. Wilber; Serge J. Belongie (NIPS, 2016)

Disentangling Nonlinear Perceptual Embeddings With Multi-Query Triplet Networks. - Andreas Veit; Serge J. Belongie; Theofanis Karaletsos (CoRR, 2016)

COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images. - Andreas Veit; Tomas Matera; Lukás Neumann; Jiri Matas; Serge J. Belongie (CoRR, 2016)

Residual Networks are Exponential Ensembles of Relatively Shallow Networks. - Andreas Veit; Michael J. Wilber; Serge J. Belongie (CoRR, 2016)

Learning from Noisy Large-Scale Datasets with Minimal Supervision. - Andreas Veit; Neil Alldrin; Gal Chechik; Ivan Krasin; Abhinav Gupta 001; Serge J. Belongie (CVPR, 2017)

Conditional Similarity Networks. - Andreas Veit; Serge J. Belongie; Theofanis Karaletsos (CVPR, 2017)

ICDAR2017 Robust Reading Challenge on COCO-Text. - Raul Gomez; Baoguang Shi; Lluis Gomez-Bigorda; Lukás Neumann; Andreas Veit; Jiri Matas; Serge J. Belongie; Dimosthenis Karatzas (ICDAR, 2017)

Crowd Research: Open and Scalable University Laboratories. - Rajan Vaish; Snehalkumar (Neil) S. Gaikwad; Geza Kovacs; Andreas Veit; Ranjay Krishna; Imanol Arrieta Ibarra; Camelia Simoiu; Michael J. Wilber; Serge J. Belongie; Sharad Goel; James Davis 001; Michael S. Bernstein (UIST, 2017)

Deep Learning is Robust to Massive Label Noise. - David Rolnick; Andreas Veit; Serge J. Belongie; Nir Shavit (CoRR, 2017)

Convolutional Networks with Adaptive Computation Graphs. - Andreas Veit; Serge J. Belongie (CoRR, 2017)

Learning to Evaluate Image Captioning. - Yin Cui; Guandao Yang; Andreas Veit; Xun Huang; Serge J. Belongie (CVPR, 2018)

Separating Self-Expression and Visual Content in Hashtag Supervision. - Andreas Veit; Maximilian Nickel; Serge J. Belongie; Laurens van der Maaten (CVPR, 2018)

Semantic Segmentation with Scarce Data. - Isay Katsman; Rohun Tripathi; Andreas Veit; Serge J. Belongie (CoRR, 2018)

Why ADAM Beats SGD for Attention Models. - Jingzhao Zhang; Sai Praneeth Karimireddy; Andreas Veit; Seungyeon Kim 001; Sashank J. Reddi; Sanjiv Kumar; Suvrit Sra (CoRR, 2019)

How To Backdoor Federated Learning. - Eugene Bagdasaryan; Andreas Veit; Yiqing Hua; Deborah Estrin; Vitaly Shmatikov (AISTATS, 2020)

Why are Adaptive Methods Good for Attention Models? - Jingzhao Zhang; Sai Praneeth Karimireddy; Andreas Veit; Seungyeon Kim 001; Sashank J. Reddi; Sanjiv Kumar; Suvrit Sra (NeurIPS, 2020)

Doubly-stochastic mining for heterogeneous retrieval. - Ankit Singh Rawat; Aditya Krishna Menon; Andreas Veit; Felix X. Yu; Sashank J. Reddi; Sanjiv Kumar (CoRR, 2020)

Improving Calibration in Deep Metric Learning With Cross-Example Softmax. - Andreas Veit; Kimberly Wilber (CoRR, 2020)

Convolutional Networks with Adaptive Inference Graphs. - Andreas Veit; Serge J. Belongie (Int. J. Comput. Vis., 2020)

RankDistil: Knowledge Distillation for Ranking. - Sashank J. Reddi; Rama Kumar Pasumarthi; Aditya Krishna Menon; Ankit Singh Rawat; Felix X. Yu; Seungyeon Kim 001; Andreas Veit; Sanjiv Kumar (AISTATS, 2021)

Understanding Robustness of Transformers for Image Classification. - Srinadh Bhojanapalli; Ayan Chakrabarti; Daniel Glasner; Daliang Li; Thomas Unterthiner; Andreas Veit (ICCV, 2021)

Long-tail learning via logit adjustment. - Aditya Krishna Menon; Sadeep Jayasumana; Ankit Singh Rawat; Himanshu Jain; Andreas Veit; Sanjiv Kumar (ICLR, 2021)

Coping with Label Shift via Distributionally Robust Optimisation. - Jingzhao Zhang; Aditya Krishna Menon; Andreas Veit; Srinadh Bhojanapalli; Sanjiv Kumar; Suvrit Sra (ICLR, 2021)

On the Reproducibility of Neural Network Predictions. - Srinadh Bhojanapalli; Kimberly Wilber; Andreas Veit; Ankit Singh Rawat; Seungyeon Kim 001; Aditya Krishna Menon; Sanjiv Kumar (CoRR, 2021)

Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation. - Srinadh Bhojanapalli; Ayan Chakrabarti; Himanshu Jain; Sanjiv Kumar; Michal Lukasik; Andreas Veit (CoRR, 2021)

Leveraging redundancy in attention with Reuse Transformers. - Srinadh Bhojanapalli; Ayan Chakrabarti; Andreas Veit; Michal Lukasik; Himanshu Jain; Frederick Liu; Yin-Wen Chang; Sanjiv Kumar (CoRR, 2021)

When does mixup promote local linearity in learned representations? - Arslan Chaudhry; Aditya Krishna Menon; Andreas Veit; Sadeep Jayasumana; Srikumar Ramalingam; Sanjiv Kumar (CoRR, 2022)

Large Language Models with Controllable Working Memory. - Daliang Li; Ankit Singh Rawat; Manzil Zaheer; Xin Wang 016; Michal Lukasik; Andreas Veit; Felix X. Yu; Sanjiv Kumar (ACL (Findings), 2023)

Teacher Guided Training: An Efficient Framework for Knowledge Transfer. - Manzil Zaheer; Ankit Singh Rawat; Seungyeon Kim 001; Chong You; Himanshu Jain; Andreas Veit; Rob Fergus; Sanjiv Kumar (ICLR, 2023)

SPEGTI: Structured Prediction for Efficient Generative Text-to-Image Models. - Sadeep Jayasumana; Daniel Glasner; Srikumar Ramalingam; Andreas Veit; Ayan Chakrabarti; Sanjiv Kumar (CoRR, 2023)

MarkovGen: Structured Prediction for Efficient Text-to-Image Generation. - Sadeep Jayasumana; Daniel Glasner; Srikumar Ramalingam; Andreas Veit; Ayan Chakrabarti; Sanjiv Kumar (CVPR, 2024)

Rethinking FID: Towards a Better Evaluation Metric for Image Generation. - Sadeep Jayasumana; Srikumar Ramalingam; Andreas Veit; Daniel Glasner; Ayan Chakrabarti; Sanjiv Kumar (CVPR, 2024)

Efficient Document Ranking with Learnable Late Interactions. - Ziwei Ji; Himanshu Jain; Andreas Veit; Sashank J. Reddi; Sadeep Jayasumana; Ankit Singh Rawat; Aditya Krishna Menon; Felix X. Yu; Sanjiv Kumar (CoRR, 2024)

LatentCRF: Continuous CRF for Efficient Latent Diffusion. - Kanchana Ranasinghe; Sadeep Jayasumana; Andreas Veit; Ayan Chakrabarti; Daniel Glasner; Michael S. Ryoo; Srikumar Ramalingam; Sanjiv Kumar (CoRR, 2024)