Search Results - Piratla, Vihari

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  1. 1
    Parameter estimation of tuberculosis transmission model using Ensemble Kalman filter across Indian states and union territories

    Parameter estimation of tuberculosis transmission model using Ensemble Kalman filter across Indian states and union territories by Narula, Pankaj, Piratla, Vihari, Bansal, Ankit, Azad, Sarita, Lio, Pietro

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  2. 2
    Robustness, Evaluation and Adaptation of Machine Learning Models in the Wild

    Robustness, Evaluation and Adaptation of Machine Learning Models in the Wild by Piratla, Vihari

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  3. 3
    Implicit Training of Energy Model for Structure Prediction

    Implicit Training of Energy Model for Structure Prediction by Shankar, Shiv, Piratla, Vihari

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  4. 4
    Untapped Potential of Data Augmentation: A Domain Generalization Viewpoint

    Untapped Potential of Data Augmentation: A Domain Generalization Viewpoint by Piratla, Vihari, Shankar, Shiv

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  5. 5
    Focus on the Common Good: Group Distributional Robustness Follows

    Focus on the Common Good: Group Distributional Robustness Follows by Piratla, Vihari, Praneeth Netrapalli, Sarawagi, Sunita

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  6. 6
    Use Perturbations when Learning from Explanations

    Use Perturbations when Learning from Explanations by Heo, Juyeon, Piratla, Vihari, Wicker, Matthew, Weller, Adrian

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  7. 7
    Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations

    Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations by Piratla, Vihari, Chakrabarty, Soumen, Sarawagi, Sunita

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  8. 8
    Estimation of Concept Explanations Should be Uncertainty Aware

    Estimation of Concept Explanations Should be Uncertainty Aware by Piratla, Vihari, Heo, Juyeon, Collins, Katherine M, Singh, Sukriti, Weller, Adrian

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  9. 9
    Efficient Domain Generalization via Common-Specific Low-Rank Decomposition

    Efficient Domain Generalization via Common-Specific Low-Rank Decomposition by Piratla, Vihari, Praneeth Netrapalli, Sarawagi, Sunita

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  10. 10
    Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time

    Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time by Nasery, Anshul, Thakur, Soumyadeep, Piratla, Vihari, De, Abir, Sarawagi, Sunita

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  11. 11
    Human-in-the-Loop Mixup

    Human-in-the-Loop Mixup by Collins, Katherine M, Bhatt, Umang, Liu, Weiyang, Piratla, Vihari, Sucholutsky, Ilia, Love, Bradley, Weller, Adrian

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  12. 12
    Topic Sensitive Attention on Generic Corpora Corrects Sense Bias in Pretrained Embeddings

    Topic Sensitive Attention on Generic Corpora Corrects Sense Bias in Pretrained Embeddings by Piratla, Vihari, Sarawagi, Sunita, Chakrabarti, Soumen

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  13. 13
    NLP Service APIs and Models for Efficient Registration of New Clients

    NLP Service APIs and Models for Efficient Registration of New Clients by Shah, Sahil, Piratla, Vihari, Chakrabarti, Soumen, Sarawagi, Sunita

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  14. 14
    Parallel Iterative Edit Models for Local Sequence Transduction

    Parallel Iterative Edit Models for Local Sequence Transduction by Awasthi, Abhijeet, Sarawagi, Sunita, Goyal, Rasna, Ghosh, Sabyasachi, Piratla, Vihari

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  15. 15
    An Analysis of Frame-skipping in Reinforcement Learning

    An Analysis of Frame-skipping in Reinforcement Learning by Kalyanakrishnan, Shivaram, Aravindan, Siddharth, Bagdawat, Vishwajeet, Bhatt, Varun, Goka, Harshith, Gupta, Archit, Krishna, Kalpesh, Piratla, Vihari

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  16. 16
    Generalizing Across Domains via Cross-Gradient Training

    Generalizing Across Domains via Cross-Gradient Training by Shankar, Shiv, Piratla, Vihari, Chakrabarti, Soumen, Chaudhuri, Siddhartha, Jyothi, Preethi, Sarawagi, Sunita

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