Kunde, Vishnu_Teja, Valmeekam, Chandra_Shekhara_Kaushik, Narayanan, Krishna, Chamberland, Jean-Francois, Kalathil, Dileep, and Shakkottai, Srinivas. Transformers are Provably Optimal In-context Estimators for Wireless Communications. Retrieved from https://par.nsf.gov/biblio/10637422.

Kunde, Vishnu_Teja, Valmeekam, Chandra_Shekhara_Kaushik, Narayanan, Krishna, Chamberland, Jean-Francois, Kalathil, Dileep, & Shakkottai, Srinivas. Transformers are Provably Optimal In-context Estimators for Wireless Communications. Retrieved from https://par.nsf.gov/biblio/10637422.

Kunde, Vishnu_Teja, Valmeekam, Chandra_Shekhara_Kaushik, Narayanan, Krishna, Chamberland, Jean-Francois, Kalathil, Dileep, and Shakkottai, Srinivas. "Transformers are Provably Optimal In-context Estimators for Wireless Communications". Country unknown/Code not available: JMLR (Journal of Machine Learning Research), Cambridge MA. https://par.nsf.gov/biblio/10637422.

@article{osti_10637422,
place = {Country unknown/Code not available}, title = {Transformers are Provably Optimal In-context Estimators for Wireless Communications}, url = {https://par.nsf.gov/biblio/10637422}, abstractNote = {}, journal = {}, publisher = {JMLR (Journal of Machine Learning Research), Cambridge MA}, author = {Kunde, Vishnu_Teja and Valmeekam, Chandra_Shekhara_Kaushik and Narayanan, Krishna and Chamberland, Jean-Francois and Kalathil, Dileep and Shakkottai, Srinivas}, }