Results 221 to 230 of about 592,913 (254)
Reinforcement learning control of quantum error correction. [PDF]
NatureSivak V, Morvan A, Broughton M, Cortiñas RG, Bausch J, Senior AW, Neeley M, Eickbusch A, Shutty N, Beni LA, Spencer JS, Heras FJ, Edlich T, Abanin D, Abbas A, Acharya R, Aigeldinger G, Alcaraz R, Alcaraz S, Andersen TI, Ansmann M, Arute F, Arya K, Askew W, Astrakhantsev N, Atalaya J, Ballard B, Bardin JC, Bates H, Bengtsson A, Karimi MB, Bilmes A, Bilodeau S, Borjans F, Bourassa A, Bovaird J, Bowers D, Brill L, Brooks P, Browne DA, Buchea B, Buckley BB, Burger T, Burkett B, Bushnell N, Busnaina J, Cabrera A, Campero J, Chang HS, Chen S, Chiaro B, Chih LY, Cleland AY, Cochrane B, Cockrell M, Cogan J, Collins R, Conner P, Cook H, Courtney W, Crook AL, Curtin B, Damyanov M, Das S, Debroy DM, Demura S, Donohoe P, Drozdov I, Dunsworth A, Ehimhen V, Elbag AM, Ella L, Elzouka M, Enriquez D, Erickson C, Ferreira VS, Flores M, Burgos LF, Forati E, Ford J, Fowler AG, Foxen B, Fukami M, Fung AWL, Fuste L, Ganjam S, Garcia G, Garrick C, Gasca R, Gehring H, Geiger R, Genois É, Giang W, Gilboa D, Goeders JE, Gonzales EC, Gosula R, de Graaf SJ, Dau AG, Graumann D, Grebel J, Greene A, Gross JA, Guerrero J, Le Guevel L, Ha T, Habegger S, Hadick T, Hadjikhani A, Hamilton MC, Harrigan MP, Harrington SD, Hartshorn J, Heslin S, Heu P, Higgott O, Hiltermann R, Huang HY, Hucka M, Hudspeth C, Huff A, Huggins WJ, Jeffrey E, Jevons S, Jiang Z, Jin X, Joshi C, Juhas P, Kabel A, Kafri D, Kang H, Kang K, Karamlou AH, Kaufman R, Kechedzhi K, Khattar T, Khezri M, Kim S, Knaut CM, Kobrin B, Kostritsa F, Kreikebaum JM, Kudo R, Kueffler B, Kumar A, Kurilovich VD, Kutsko V, Lacroix N, Landhuis D, Lange-Dei T, Langley BW, Laptev P, Lau KM, Ledford J, Lee J, Lee K, Lester BJ, Leung W, Li L, Li WY, Li M, Lill AT, Livingston WP, Lloyd MT, Locharla A, De Lorenzo L, Lundahl D, Lunt A, Madhuk S, Maiti A, Maloney A, Mandrá S, Martin LS, Martin O, Mascot E, Das PM, Maslov D, Mathews M, Maxfield C, McClean JR, McEwen M, Meeks S, Miao KC, Minev ZK, Molavi R, Molina S, Montazeri S, Neill C, Newman M, Nguyen A, Nguyen M, Ni CH, Niu MY, Oas L, Orosco R, Ottosson K, Pagano A, Paolo AD, Peek S, Peterson D, Pizzuto A, Portoles E, Potter R, Pritchard O, Qian M, Quintana C, Ranadive A, Reagor MJ, Resnick R, Rhodes DM, Riley D, Roberts G, Rodriguez R, Ropes E, De Rose LB, Rosenberg E, Rosenfeld E, Rosenstock D, Rossi E, Roushan P, Rower DA, Salazar R, Sankaragomathi K, Sarihan MC, Satzinger KJ, Schaefer M, Schroeder S, Schurkus HF, Shahingohar A, Shearn MJ, Shorter A, Shvarts V, Small S, Smith WC, Sobel DA, Spells B, Springer S, Sterling G, Suchard J, Szasz A, Sztein A, Taylor M, Thiruraman JP, Thor D, Timucin D, Tomita E, Torres A, Torunbalci MM, Tran H, Vaishnav A, Vargas J, Vdovichev S, Vidal G, Heidweiller CV, Voorhees M, Waltman S, Waltz J, Wang SX, Ware B, Watson JD, Wei Y, Weidel T, White T, Wong K, Woo BWK, Wood CJ, Woodson M, Xing C, Yao ZJ, Yeh P, Ying B, Yoo J, Yosri N, Young E, Young G, Zalcman A, Zhang R, Zhang Y, Zhu N, Zobrist N, Zou Z, Babbush R, Bacon D, Boixo S, Chen Y, Chen Z, Devoret M, Hansen M, Hilton J, Jones C, Kelly J, Korotkov AN, Lucero E, Megrant A, Neven H, Oliver WD, Ramachandran G, Smelyanskiy V, Klimov PV. +298 moreeuropepmc +1 more sourceRiTeK: A Dataset for Large Language Models Complex Reasoning over Textual Knowledge Graphs in Medicine. [PDF]
Find ACL ACLHuang J, Li M, Yao Z, Li D, Zhang Y, Yang Z, Xiao Y, Ouyang F, Li X, Han S, Yu H. +10 moreeuropepmc +1 more sourceSome of the next articles are maybe not open access.Related searches:
The Relationship Between Logical Entropy and Shannon Entropy
SpringerBriefs in Philosophy, 2021 This chapter is focused on developing the basic notion of Shannon entropy, its interpretation in terms of distinctions, i.e., the minimum average number of yes-or-no questions that must be answered to distinguish all the “messages.” Thus Shannon entropy is also a quantitative indicator of information-as-distinctions, and, accordingly, a “dit-bit ...David Ellermanexaly +2 more sources