Robust Negative Sampling for Network Embedding. - Mohammadreza Armandpour; Patrick Ding; Jianhua Z. Huang; Xia Hu (AAAI, 2019)

DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs. - Ali Sadeghian; Mohammadreza Armandpour; Patrick Ding; Daisy Zhe Wang (NeurIPS, 2019)

Convex Polytope Trees. - Mohammadreza Armandpour; Mingyuan Zhou (CoRR, 2020)

ChronoR: Rotation Based Temporal Knowledge Graph Embedding. - Ali Sadeghian; Mohammadreza Armandpour; Anthony M. Colas; Daisy Zhe Wang (AAAI, 2021)

Partition-Guided GANs. - Mohammadreza Armandpour; Ali Sadeghian; Chunyuan Li; Mingyuan Zhou (CVPR, 2021)

Deep Personalized Glucose Level Forecasting Using Attention-based Recurrent Neural Networks. - Mohammadreza Armandpour; Brian Kidd; Yu Du; Jianhua Z. Huang (IJCNN, 2021)

Convex Polytope Trees and its Application to VAE. - Mohammadreza Armandpour; Ali Sadeghian; Mingyuan Zhou (NeurIPS, 2021)

Bayesian Graph Contrastive Learning. - Arman Hasanzadeh; Mohammadreza Armandpour; Ehsan Hajiramezanali; Mingyuan Zhou; Nick Duffield; Krishna Narayanan 001 (CoRR, 2021)

SYNT++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition. - Ting-Yao Hu; Mohammadreza Armandpour; Ashish Shrivastava 001; Jen-Hao Rick Chang; Hema Koppula; Oncel Tuzel (ICASSP, 2022)

Deep Spatio-Temporal Wind Power Forecasting. - Jiangyuan Li; Mohammadreza Armandpour (ICASSP, 2022)

Gluformer: Transformer-based Personalized glucose Forecasting with uncertainty quantification. - Renat Sergazinov; Mohammadreza Armandpour; Irina Gaynanova (ICASSP, 2023)

Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond. - Mohammadreza Armandpour; Ali Sadeghian; Huangjie Zheng; Amir Sadeghian; Mingyuan Zhou (CoRR, 2023)

TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining. - Jeffrey Li; Mohammadreza Armandpour; Iman Mirzadeh; Sachin Mehta; Vaishaal Shankar; Raviteja Vemulapalli; Samy Bengio; Oncel Tuzel; Mehrdad Farajtabar; Hadi Pouransari; Fartash Faghri (ACL (1), 2025)