Recurrent Marked Temporal Point Processes: Embedding Event History to Vector. - Nan Du 002; Hanjun Dai; Rakshit Trivedi; Utkarsh Upadhyay; Manuel Gomez-Rodriguez; Le Song (KDD, 2016)

Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions. - Yichen Wang 001; Nan Du 002; Rakshit Trivedi; Le Song (NIPS, 2016)

Recurrent Coevolutionary Latent Feature Processes for Continuous-Time Recommendation. - Hanjun Dai; Yichen Wang 001; Rakshit Trivedi; Le Song (DLRS@RecSys, 2016)

Recurrent Coevolutionary Feature Embedding Processes for Recommendation. - Hanjun Dai; Yichen Wang 001; Rakshit Trivedi; Le Song (CoRR, 2016)

Fake News Mitigation via Point Process Based Intervention. - Mehrdad Farajtabar; Jiachen Yang; Xiaojing Ye; Huan Xu; Rakshit Trivedi; Elias B. Khalil; Shuang Li 002; Le Song; Hongyuan Zha (ICML, 2017)

Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs. - Rakshit Trivedi; Hanjun Dai; Yichen Wang 001; Le Song (ICML, 2017)

Tweeting about journal articles: Engagement, marketing or just gibberish? - Nicolás Robinson-García; Rakshit Trivedi; Rodrigo Costas 001; Kimberley R. Isett; Julia E. Melkers; Diana Hicks (CoRR, 2017)

Know-Evolve: Deep Reasoning in Temporal Knowledge Graphs. - Rakshit Trivedi; Hanjun Dai; Yichen Wang 001; Le Song (CoRR, 2017)

Deep Mean Field Games for Learning Optimal Behavior Policy of Large Populations. - Jiachen Yang; Xiaojing Ye; Rakshit Trivedi; Huan Xu; Hongyuan Zha (CoRR, 2017)

LinkNBed: Multi-Graph Representation Learning with Entity Linkage. - Rakshit Trivedi; Bunyamin Sisman; Xin Luna Dong; Christos Faloutsos; Jun Ma 029; Hongyuan Zha (ACL (1), 2018)

Learning Deep Mean Field Games for Modeling Large Population Behavior. - Jiachen Yang; Xiaojing Ye; Rakshit Trivedi; Huan Xu; Hongyuan Zha (ICLR, 2018)

Representation Learning over Dynamic Graphs. - Rakshit Trivedi; Mehrdad Farajtabar; Prasenjeet Biswal; Hongyuan Zha (CoRR, 2018)

DyRep: Learning Representations over Dynamic Graphs. - Rakshit Trivedi; Mehrdad Farajtabar; Prasenjeet Biswal; Hongyuan Zha (ICLR (Poster), 2019)

GraphOpt: Learning Optimization Models of Graph Formation. - Rakshit Trivedi; Jiachen Yang; Hongyuan Zha (ICML, 2020)

Learning Strategic Network Emergence Games. - Rakshit Trivedi; Hongyuan Zha (NeurIPS, 2020)

Learning Dynamic Processes over graphs. - Rakshit Trivedi (2020)

Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning. - Jiachen Yang; Ethan Wang; Rakshit Trivedi; Tuo Zhao; Hongyuan Zha (AAMAS, 2022)

CrowdPlay: Crowdsourcing Human Demonstrations for Offline Learning. - Matthias Gerstgrasser; Rakshit Trivedi; David C. Parkes (ICLR, 2022)

Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models. - Kartik Sharma; Rakshit Trivedi; Rohit Sridhar; Srijan Kumar (KDD, 2023)

Diffuse, Sample, Project: Plug-And-Play Controllable Graph Generation. - Kartik Sharma; Srijan Kumar; Rakshit Trivedi (ICML, 2024)

Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence. - Rakshit Trivedi; Akbir Khan; Jesse Clifton; Lewis Hammond; Edgar A. Duéñez-Guzmán; Dipam Chakraborty; John P. Agapiou; Jayd Matyas; Alexander Sasha Vezhnevets; Barna Pásztor; Yunke Ao; Omar G. Younis; et al. (NeurIPS, 2024)

The AI Agent Index. - Stephen Casper; Luke Bailey; Rosco Hunter; Carson Ezell; Emma Cabalé; Michael Gerovitch; Stewart Slocum; Kevin Wei; Nikola Jurkovic; Ariba Khan; Phillip J. K. Christoffersen; A. Pinar Ozisik; et al. (CoRR, 2025)

Efficient Knowledge Probing of Large Language Models by Adapting Pre-trained Embeddings. - Kartik Sharma; Yiqiao Jin; Rakshit Trivedi; Srijan Kumar (CoRR, 2025)