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AI-Dictionary

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fully connected connection

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autonomous flight control

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discriminative deep

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adversarial network algorithm

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classical autonomous vehicle

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traditional autonomous vehicle

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dvd gan architecture

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dvd gan improvement

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accurate oriented bounding

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-1.3719844818115234, -0.742787778377533, -0.09863831102848053]

classical deontic logic

[-0.8278163075447083, 1.3103599548339844, -0.5338768362998962, -0.7939873933792114, 0.6916041970252991, -0.9222100973129272, 1.365360140800476, -0.1848648488521576, -0.3232007920742035, 1.230133295059204, 0.5833233594894409, -0.5047364830970764, -0.5299278497695923, -0.7325901389122009, -0.2893477976322174, -0.959912121295929, -0.1867065578699112, 0.7480794191360474, 0.9740912318229675, -0.9079962372779846, -0.2309635728597641, 0.5345454812049866, -1.2618046998977661, 0.6148460507392883, 0.48568135499954224, 1.318892240524292, -0.8702805638313293, 0.17500342428684235, 0.9686505198478699, 2.089312791824341, -0.06600700318813324, -0.806427001953125, -0.004096013028174639, 0.12401372939348221, -1.6551567316055298, 0.20385801792144775, -0.7587384581565857, -0.307232528924942, -0.666786253452301, 1.1179537773132324, -0.005643297452479601, -0.059377823024988174, 0.27767691016197205, -1.7398754358291626, -1.1810920238494873, 1.269119143486023, 0.43781644105911255, -0.18568776547908783, 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1.1210414171218872, -1.878032922744751, -0.8832157850265503, 0.010057986713945866, -0.09579969197511673, 0.0135778384283185, 0.5253359079360962, 0.7756261825561523, -0.3057127594947815, -0.19087408483028412, 0.17644748091697693, 0.6375333666801453, 0.697166383266449, 1.4862934350967407, -0.5643972754478455, 1.3120992183685303, -0.11589821428060532, 1.0574872493743896, -1.1980268955230713, -1.3567641973495483, -0.18144948780536652, -0.4831240773200989, -0.8460742235183716, 0.19493350386619568, -0.7417203783988953, 0.07075238972902298, -0.6198490858078003, 0.7572194337844849, 0.7245743870735168, -0.280971497297287, 1.185599684715271, 0.6533116698265076, -0.33175206184387207, 1.2449318170547485, -0.844243586063385, 1.2834360599517822, -0.06733622401952744, 0.12928983569145203, 0.3842735290527344, -0.8444889783859253, -0.15349040925502777, 1.7998933792114258, 0.6461533308029175, -0.793321967124939, 0.17919676005840302, 0.5622121691703796, 0.28097841143608093, -1.2996553182601929, 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-0.3925071060657501, 1.9093542098999023, 0.715930163860321, 1.3836767673492432, 0.30398717522621155, -0.1952085942029953, 0.5101945996284485, 0.7569240927696228, 0.6369648575782776, 1.2394543886184692, 0.9887226819992065, 0.36339235305786133, 1.3148351907730103, 0.7719216346740723, 0.41940543055534363, 0.7312332391738892, 0.31446701288223267, -1.572954773902893, 0.24612310528755188, -0.5789312720298767, 0.6483708620071411, -2.4891932010650635, -1.8733932971954346, -0.710600733757019, 1.5213247537612915, 1.6806401014328003, -0.37614741921424866, -0.07250930368900299, 0.25616779923439026, 0.24752077460289001, 0.05695815756917, 0.27243444323539734, -1.0516184568405151, -0.33469969034194946, -0.292009562253952, 0.21372239291667938, 1.1684943437576294, -0.7919875979423523, 1.3658902645111084, 8.039727210998535, 0.3893391788005829, -0.02722659520804882, 0.6896407008171082, -0.3019101321697235, -0.09635070711374283, -0.6973611116409302, 0.9479390978813171, -0.37692174315452576, -0.272996187210083, 0.7418355941772461, -0.6977149844169617, 0.9481605291366577, 0.8716571927070618, 0.25773629546165466, -0.877557635307312, -2.024146556854248, 0.589237630367279, -0.401458740234375, -0.9205049276351929, -0.5020520687103271, 0.2611233592033386, 1.0441205501556396, -0.24395756423473358, -0.7940327525138855, 0.12755341827869415, 1.5986682176589966, -0.0728415921330452, 1.419442057609558, 0.19756236672401428, 0.07636427879333496, -0.0842655822634697, 1.2206324338912964, 0.18562884628772736, -0.5134328007698059, -0.4390457272529602, -0.708939254283905, -0.39139673113822937, 0.6256254315376282, 0.28936758637428284, -0.08613907545804977, 0.16823755204677582, 0.43009281158447266, 0.375029593706131, 0.04191499948501587, 0.5922113656997681, -1.2073220014572144, -0.5260455012321472, -0.39319029450416565, -0.09799859672784805, 0.5930789709091187, -0.7185810208320618, 0.4941325783729553, -0.04935380816459656, -0.5258238911628723, 0.9412419199943542, -0.3846947252750397, 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-0.414670467376709, -0.5518129467964172, 0.9161224365234375]

deontic logic

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1.0030866861343384]

fine tuning process

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wsol

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lightweight and scalable

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regularization coefficient

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regularization weight

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flatter local minimum

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-0.7187896370887756, -0.0744536742568016]

highly general approach

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convolutional residual neural

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exact ground truth

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previous generative adversarial

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exploration

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weight decay term

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object segmentation model

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dialogue structure

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existing big data

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modern big data

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0.1847112774848938]

standard backpropagation training

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xgpt

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multiscopic

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data efficient

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image scale augmentation

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reasonable training speed

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knowledge base paradigm

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current word sense

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based word sense

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suitable word sense

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sense induction wsi

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biggan

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spectrally normalised gan

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biggan image generator

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regular random search

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knowledge representation approach

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0.0093003511428833, 1.0164806842803955]

additive utility function

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exponential activation function

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general relational data

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0.033476244658231735, 0.13857758045196533]

relational algebra

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fully weakly supervised

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large scale weak supervision

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policy search problem

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generative adversarial feedback

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fair abstractive summarization

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improved contrastive learning

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recognising object

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reactor accident

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pressurized water reactor

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intensive care iii

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efficient gpu

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mobile gpu aware moga

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multi spectral channel

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spectrum measurement

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wideband spectrum

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classic belief propagation

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squashing activation function

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-0.8296361565589905, -0.2988162934780121]

noise reduction method

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graph embedding problem

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adaptive batch normalization

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strong functional dependency

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pulse wave

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saliency mapping

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data ablation

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-0.7218238115310669, 0.41965752840042114]

medical image classifier

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accurate segmentation map

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segmentation refinement

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1.0246293544769287]

accurate fine grained segmentation

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fine grained segmentation

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recently popular approach

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relational learning

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descriptive variational autoencoder

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hybrid variational autoencoder

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split variational autoencoder

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trainable weight matrix

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