| 2025 | AAAI | Active Reinforcement Learning Strategies for Offline Policy Improvement. | Ambedkar Dukkipati, Ranga Shaarad Ayyagari, Bodhisattwa Dasgupta, Parag Dutta, Prabhas Reddy Onteru |
| 2025 | AAAI | Deep Representation Learning for Forecasting Recursive and Multi-Relational Events in Temporal Networks. | Tony Gracious, Ambedkar Dukkipati |
| 2025 | AAAI | Neural Temporal Point Processes for Forecasting Directional Relations in Evolving Hypergraphs. | Tony Gracious, Arman Gupta, Ambedkar Dukkipati |
| 2025 | ICCV | Semi-Supervised Deep Transfer for Regression Without Domain Alignment. | Mainak Biswas, Ambedkar Dukkipati, Devarajan Sridharan |
| 2025 | ICCV | One Encoder to Rule Them All: Representation Learning for Model-Free Visual Reinforcement Learning Using Fourier Neural Operators. | Parag Dutta, Mohd Ayyoob, Shalabh Bhatnagar, Ambedkar Dukkipati |
| 2024 | WACV | Causal Feature Alignment: Learning to Ignore Spurious Background Features. | Rahul Venkataramani, Parag Dutta, Vikram Melapudi, Ambedkar Dukkipati |
| 2023 | AAAI | Dynamic Representation Learning with Temporal Point Processes for Higher-Order Interaction Forecasting. | Tony Gracious, Ambedkar Dukkipati |
| 2023 | ACML | Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain. | Parag Dutta, Kawin Mayilvaghanan, Pratyaksha Sinha, Ambedkar Dukkipati |
| 2023 | ISIT | Risk-Averse Combinatorial Semi-Bandits. | Ranga Shaarad Ayyagari, Ambedkar Dukkipati |
| 2023 | WSC | A Multi-Team Multi-Model Collaborative Covid-19 Forecasting Hub for India. | Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav V. Marathe, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Ambedkar Dukkipati, Tony Gracious, Shubham Gupta, Nihesh Rathod, Rajesh Sundaresan, Sarath Yasodharan, Kantha Rao Bhimala, Vidyadhar Mudkavi, Gopal Krishna Patra, Siva Athreya |
| 2022 | IROS | Learning Skills to Navigate without a Master: A Sequential Multi-Policy Reinforcement Learning Algorithm. | Ambedkar Dukkipati, Rajarshi Banerjee, Ranga Shaarad Ayyagari, Dhaval Parmar Udaybhai |
| 2021 | AAAI | Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs. | Tony Gracious, Shubham Gupta, Arun Kanthali, Rui M. Castro, Ambedkar Dukkipati |
| 2021 | NAACL | Active² Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation. | Rishi Hazra, Parag Dutta, Shubham Gupta, Mohammed Abdul Qaathir, Ambedkar Dukkipati |
| 2019 | AAAI | A Generative Model for Dynamic Networks with Applications. | Shubham Gupta, Gaurav Sharma, Ambedkar Dukkipati |
| 2019 | ICDM | CUDA: Contradistinguisher for Unsupervised Domain Adaptation. | Sourabh Balgi, Ambedkar Dukkipati |
| 2019 | WACV | Skip Residual Pairwise Networks With Learnable Comparative Functions for Few-Shot Learning. | Akshay Mehrotra, Ambedkar Dukkipati |
| 2019 | WACV | Learning to Segment With Image-Level Supervision. | Gaurav Pandey, Ambedkar Dukkipati |
| 2018 | ISIT | On Consistency of Compressive Spectral Clustering. | Muni Sreenivas Pydi, Ambedkar Dukkipati |
| 2018 | NAACL | Learning beyond Datasets: Knowledge Graph Augmented Neural Networks for Natural Language Processing. | K. M. Annervaz, Somnath Basu Roy Chowdhury, Ambedkar Dukkipati |
| 2017 | ICDM | Unsupervised Feature Learning with Discriminative Encoder. | Gaurav Pandey, Ambedkar Dukkipati |
| 2017 | ICML | Attentive Recurrent Comparators. | Pranav Shyam, Shubham Gupta, Ambedkar Dukkipati |
| 2017 | IJCNN | Variational methods for conditional multimodal deep learning. | Gaurav Pandey, Ambedkar Dukkipati |
| 2016 | ICML | On collapsed representation of hierarchical Completely Random Measures. | Gaurav Pandey, Ambedkar Dukkipati |
| 2016 | IJCNN | Mixture modeling with compact support distributions for unsupervised learning. | Ambedkar Dukkipati, Debarghya Ghoshdastidar, Jinu Krishnan |
| 2015 | AAAI | Spectral Clustering Using Multilinear SVD: Analysis, Approximations and Applications. | Debarghya Ghoshdastidar, Ambedkar Dukkipati |
| 2015 | ICML | A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning. | Debarghya Ghoshdastidar, Ambedkar Dukkipati |
| 2014 | AISTATS | To go deep or wide in learning? | Gaurav Pandey, Ambedkar Dukkipati |
| 2014 | CVPR | Spectral Clustering with Jensen-Type Kernels and Their Multi-point Extensions. | Debarghya Ghoshdastidar, Ambedkar Dukkipati, Ajay P. Adsul, Aparna S. Vijayan |
| 2014 | ICML | Learning by Stretching Deep Networks. | Gaurav Pandey, Ambedkar Dukkipati |
| 2013 | AAAI | On Power-Law Kernels, Corresponding Reproducing Kernel Hilbert Space and Applications. | Debarghya Ghoshdastidar, Ambedkar Dukkipati |
| 2013 | ICDM | Generative Maximum Entropy Learning for Multiclass Classification. | Ambedkar Dukkipati, Gaurav Pandey, Debarghya Ghoshdastidar, Paramita Koley, D. M. V. Satya Sriram |
| 2013 | ISIT | Minimum description length principle for maximum entropy model selection. | Gaurav Pandey, Ambedkar Dukkipati |
| 2012 | CASC | An Algebraic Characterization of Rainbow Connectivity. | Prabhanjan Vijendra Ananth, Ambedkar Dukkipati |
| 2012 | ISIT | q-Gaussian based Smoothed Functional algorithms for stochastic optimization. | Debarghya Ghoshdastidar, Ambedkar Dukkipati, Shalabh Bhatnagar |
| 2012 | ISIT | A two stage selective averaging LDPC decoding. | A. Dinesh Kumar, Ambedkar Dukkipati |
| 2011 | ISSAC | Border basis detection is NP-complete. | Prabhanjan Vijendra Ananth, Ambedkar Dukkipati |
| 2010 | CASC | An Algebraic Implicitization and Specialization of Minimum KL-Divergence Models. | Ambedkar Dukkipati, Joel George Manathara |
| 2010 | ICPR | Maximum Entropy Model Based Classification with Feature Selection. | Ambedkar Dukkipati, Abhay Kumar Yadav, M. Narasimha Murty |
| 2010 | ISITA | On Kolmogorov-Nagumo averages and nonextensive entropy. | Ambedkar Dukkipati |
| 2009 | ISIT | Embedding maximum entropy models in algebraic varieties by Grbner bases methods. | Ambedkar Dukkipati |
| 2005 | CEC | Information theoretic justification of Boltzmann selection and its generalization to Tsallis case. | Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar |
| 2005 | ISIT | Properties of Kullback-Leibler cross-entropy minimization in nonextensive framework. | Ambedkar Dukkipati, Narasimha Murty Musti, Shalabh Bhatnagar |
| 2004 | CEC | Cauchy annealing schedule: an annealing schedule for Boltzmann selection scheme in evolutionary algorithms. | Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar |
| 2003 | CEC | Quotient evolutionary space: abstraction of evolutionary process w.r.t macroscopic properties. | Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar |
| 2002 | CEC | Selection by parts: 'selection in two episodes' in evolutionary algorithms. | Ambedkar Dukkipati, M. Narasimha Murty |